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Become a part of our caring community and help us put health first
Become a key driver in shaping the future of AI-powered healthcare. We are looking for a Principal Applied AI Engineer, a technical leader who thrives in ambiguous, high-impact environments and is motivated by solving real problems with pragmatic, elegant, and scalable solutions. This position reports into the AI platform team, ensuring close alignment with platform strategy and delivery. It is for someone who wants autonomy, influence, and the responsibility of setting a high bar for engineering excellence.

Become a key driver in shaping the future of AI-powered healthcare. We are looking for a Principal Applied AI Engineer, a technical leader who thrives in ambiguous, high-impact environments and is motivated by solving real problems with pragmatic, elegant, and scalable solutions. This position reports into the AI platform team, ensuring close alignment with platform strategy and delivery. It is for someone who wants autonomy, influence, and the responsibility of setting a high bar for engineering excellence.

WhatYou'llDo

Lead the design and build of advanced generative AI systems,spanning LLM-powered applications, multi-agent workflows, RAG, and domain-specific reasoning engines.Architect and own robust APIs and platform capabilities that bring AI toreal businessworkflows at enterprise scale.Drive the engineering of high-quality data,feature, and evaluation pipelines that support reliable and continuously improving AI behavior.Partner with data scientists, platform engineers, and product leaders to transform conceptual ideas into resilient, testable, observable production systems.Set engineering standards and elevate team culture, emphasizing clarity, craftsmanship, iteration, and objective measures of excellence.Mentor other engineers and guide teams through complex technical decision-making.Serve as a thought leader on the practical application of generative AI technologies, emerging pa

Founded in 2012, H2O.ai is on a mission to democratize AI. As the world’s leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built GenAI applications on their private data. With a focus on Sovereign AI—secure, compliant, and infrastructure-flexible deployments—H2O.ai delivers solutions that align with the highest standards of data privacy and control.

Our open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Chipotle, Workday, Progressive Insurance, and NIH.

H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS, Google Cloud Platform (GCP), VAST Data and MinIO. H2O.ai’s AI for Good program supports nonprofit groups, foundations, and communities in advancing education, healthcare, and environmental conservation. With a vibrant community of 2 million data scientists worldwide, H2O.ai aims to co-create valuable AI applications for all users.

H2O.ai has raised 256 million from investors, including Commonwealth Bank, NVIDIA, Goldman Sachs, Wells Fargo, Capital One, Nexus Ventures and New York Life.

For more information, visit www.h2o.ai.

The Opportunity

We are looking for a Senior AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one.

You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes.

What You

Sr. AI Engineer – Agent Orchestration

A high-growth technology company building AI-powered software for US government customers is hiring a Senior AI Engineer focused on agent workflow orchestration. The company’s AI agent has seen rapid adoption, and the team is now pushing it to handle increasingly complex, multi-step tasks either fully autonomously or in a human-in-the-loop mode.

This role is squarely backend and systems-focused. You’ll be designing how an AI agent plans, sequences, and executes long-running workflows — coordinating across multiple tools, data sources, and sub-agents to complete jobs that today require hours of manual work. Think of it as building the brain and nervous system of the agent, not the hands.

What You’ll Do

Architect and build the workflow engine that powers multi-step agent task execution — including planning, sequencing, branching, error recovery, and human handoff pointsDesign and implement multi-agent coordination patterns: routing between specialized sub-agents, managing shared memory and context, and orchestrating parallel workstreamsBuild scalable tool-use infrastructure that lets agents dynamically discover, select, and chain tools based on task requirementsOwn reliability and observability for long-horizon agent tasks — designing checkpointing, retry strategies, and evaluation harnesses that catch failures before users doDefine and enforce the technical architecture and engineering standards for agentic systems across the platform

What We’re Looking For

You have built an LLM reliably completing complex, multi-step tasks in production — not just single-turn Q&A, but real workflows with branching logic, tool calls, and failure handlingDeep experience with workflow orchestration patterns (DAGs, state machines, event-driven architectures) applied to LLM-powered systemsHands-on experience with agent frameworks (Claude Agent SDK, OpenAI Agent SDK, LangGraph, or similar)Strong understanding of LLM reliability e

About Autonomize AI

Autonomize AI is revolutionizing healthcare by streamlining knowledge workflows with AI. We reduce administrative burdens and elevate outcomes, empowering professionals to focus on what truly matters — improving lives. We're growing fast and looking for bold, driven teammates to join us.

The Opportunity

We're looking for a hands-on ML/LLM Engineer who’s excited to ship real-world applications — not just benchmarks. You’ll help us build and optimize AI-native systems that blend structured and unstructured data to power decisions in high-stakes domains. This is a mid to senior-level role for someone who’s ready to go deep on applied ML problems — from retrieval to routing to generation — and ship solutions that deliver impact.

What you'll do

Own and optimize pipelines that combine classical ML and LLM-based systems (RAG, scoring, summarization, etc.)

Fine-tune and evaluate LLMs using both open-source and proprietary data

Collaborate with product and engineering teams to build real-world applications in healthcare and biopharma

Implement retrieval strategies, prompt chaining, and inference orchestration for production use cases

Monitor and improve model quality, latency, explainability, and safety

Stay ahead of the curve in LLM evaluation, tuning, and agent-based architectures

Qualifications

3–6 years of experience in applied ML, with at least 1–2 years working with LLMs

Strong Python skills and familiarity with ML/LLM frameworks (PyTorch, Transformers, LangChain, LlamaIndex, etc.)

Comfort with embeddings, vector search, retrieval pipelines, and prompt tuning

Bias for experimentation, clarity, and pushing things into production — fast

Understanding of responsible AI practices, model evaluation, and observability

Experience in healthcare, compliance-sens

Hi Professionals,

Title: Healthcare Senior NLP / LLM Engineer (MLOps & AWS)-Onsite Role,Need Local to TXExperience: 7+ Years
Location: Houston, TX (3 days/week onsite)

Mandatory Skills:

Strong expertise in NLP, Machine Learning, and Deep LearningProficiency in Python for ML/NLP solution developmentHands-on experience with LLMs, prompt engineering, and agentic workflows (e.g., LangGraph)Solid knowledge of data preprocessing, feature engineering, and data validationStrong MLOps skills: model versioning, CI/CD, pipelines, monitoring, retrainingExperience with Docker and KubernetesProficiency in SQL for data analysis and transformationExperience with AWS (EMR, Spark, PySpark, Bedrock)Knowledge of PostgreSQL or MySQLStrong understanding of testing, error analysis, and model validation "Disclaimer: E-Solutions Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state and local laws. We especially invite women, minorities, veterans, and individuals with disabilities to apply. EEO/AA/M/F/Vet/Disability.”

Healthcare Senior NLP / LLM Engineer (MLOps & AWS)-Onsite Role,Need Local to TX1AWS,NLP,health OR Healthcare,MLOps,LLMN/AC2CUnited States

About Quizlet:

At Quizlet, our mission is to help every learner achieve their outcomes in the most effective and delightful way. We’re a $1B+ learning platform used by two-thirds of U.S. high school students and half of college students, powering over 1 billion learning interactions each week.

We blend cognitive science with machine learning to personalize and enhance the learning experience for students, professionals, and lifelong learners alike. We’re energized by the potential to power more learners through multiple approaches and various tools.

Let’s Build the Future of Learning

Join us to design and deliver AI-powered learning tools that scale across the world and unlock human potential.

About the Team (Applied AI):

Our mission is to invent and deploy the next generation of intelligent, personalized, and adaptive learning experiences. We’re consolidating AI efforts across the company into a unified portfolio and are accountable for a disproportionate share of Quizlet’s growth and product differentiation. You’ll partner closely with Product, Data Science, and the AI & Data Platform to deliver an AI‑driven learning coach that’s recognized as best‑in‑class.

About the Role:

As an Applied AI Engineer, you will be working at the forefront of our AI strategy, shaping Quizlet’s AI develop in one of the two complementary domains:

Personalization & Ranking – retrieval and ranking systems that match learners with the right content, experiences, and monetization moments across surfaces (search, feed, notifications, ads).

Generative AI & Agentic Systems – LLM‑powered tutoring, content understanding/synthesis, and tools that boost learner outcomes and creator productivity.

You will work on a variety of models and modeling systems (from Two‑Tower retrieval and multi‑task rankers to RAG/LLM pipelines), ensure robust evaluation and responsible deployment

We’re happy to share that this is an onsite position in either ou

GenAI / Agentic AI Engineer

Wilmington, DE - OPEN TO RELOCATION CANDIDATES

Hybrid: 3 days onsite
12-month contract (extension possible)
$68-70/hr W2 – NO CTC NO THIRD PARTY

Must be currently authorized to work in the U.S.

We are able to support H-1B transfer candidates, but are
unable to consider OPT/CPT candidates

Required Skills

3+ years experience in Generative AI / LLM / Agentic AI
Strong Python (must-have): APIs, async, microservices, distributed systems
Experience building RAG pipelines, embeddings, vector search, LLM orchestration
Experience with FastAPI / Flask
Hands-on GCP + Kubernetes/OpenShift
CI/CD + DevOps tooling experience
Experience working in enterprise or regulated environments
Ability to work independently and drive AI solutions
LangChain / LlamaIndex – nice to have -NOT REQUIRED

Day to Day

Build Generative AI and Agentic AI systems, including LLM-based autonomous agents and multi-agent workflows
Design and implement RAG pipelines (embeddings, vector search, retrieval, grounding, prompt engineering)
Develop LLM orchestration systems (function calling, tool use, guardrails, evaluation, safety controls)
Build Python-based AI microservices and APIs using FastAPI / Flask
Work on distributed AI systems supporting high-scale inference and retrieval workloads
Develop and manage MCP (Model Context Protocol) servers and context frameworks
Deploy AI solutions on GCP (Vertex AI, GKE, Cloud Run) and OpenShift/Kubernetes
Build and maintain CI/CD pipelines for AI services in enterprise environments
Work with vector databases (Pinecone, Redis, pgVector, MongoDB Atlas Vector Search, etc.)
Ensure security, governance, compliance, and responsible AI standards (banking environment)

Lead AI Engineer (AI Foundations, LLM Core and Agentic AI)

Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

Design, develop, test, deploy, and support AI software component

Lead AI Engineer (AI Foundations, LLM Core and Agentic AI)

Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

Design, develop, test, deploy, and support AI software components

Job DescriptionJoin a dynamic and fast-evolving team that is building next-generation AI-based tools and agent systems for the construction Industry. Our AI and Data Team is focused on designing intelligent AI agents and copilots using modern AI/ML techniques.

You will work closely with cross-functional teams, including business stakeholders, data engineers, and technical leads, to ensure alignment between business needs and data architecture and define data models for specific focus areas.

ResponsibilitiesBuild end-to-end Gen AI solutions - develop, refine, and implement advanced Gen AI models and ensure the successful delivery of projects.Develop and execute comprehensive plans to integrate AI technologies into business processes, aimed at enhancing operational efficiency and boosting employee productivity.Utilize Python and other data manipulation languages proficiently to prepare and manipulate data.Understand the business requirements and translate into Gen AI solution design that successfully meets the business objectives.Collaborate with stakeholders, present findings to non-technical audiences and provide strategic recommendations.Ensure the scalability, reliability, and security of AI solutions by implementing best practices for AI model development, deployment, and maintenance.Drive innovation by exploring new AI applications and solutions that can benefit the enterprise, leading research and development efforts to keep DPR at the forefront of AI technology.Follow the roadmap for AI initiatives, ensuring they align with organizational goals and show measurable impact.

QualificationsAt least 3 years of experience with Software Development, Machine Learning.At least 2 years of experience Generative AI, specifically with Large Language Models (LLM).Experience with generative AI concepts such as Retrieval-Augmented Generation (RAG), agentic workflows, training LLMs with structured and unstructured data sets.Experience with Data Connectors and API gateways

Lead AI Engineer (FM Hosting, LLM Inference)

Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

Design, develop, test, deploy, and support AI software components including foun

Job Summary

As an LLM Engineer at our forward-thinking education technology company, you will design, develop, and optimize large language model solutions that transform digital learning experiences. The ideal candidate is innovative and technically skilled, with a passion for applying AI to enhance educational content, personalized learning, and academic support tools. You will collaborate with cross-functional teams to deliver scalable, ethical, and high-impact LLM-powered solutions tailored to the needs of students and educators.

Must-Haves:

We are seeking a candidate with proven experience developing and deploying large language models, ideally with applications in education or e-learning. You must be proficient in Python and familiar with leading ML/AI frameworks (such as TensorFlow, PyTorch, or Hugging Face Transformers). A strong understanding of NLP, prompt engineering, and model evaluation is essential. Experience with cloud platforms and a solid grasp of data privacy and ethical AI in education are highly valued. Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders are required.

Responsibilities:

Design, develop, and optimize LLM-based applications for educational use cases, such as adaptive tutoring, content generation, and automated assessment.
Fine-tune, evaluate, and maintain LLMs using relevant educational datasets and benchmarks.
Implement prompt engineering and in-context learning strategies to improve model performance and user experience.
Collaborate with educators, product managers, and engineers to align LLM solutions with pedagogical goals and user needs.
Develop and maintain robust, scalable APIs and services for LLM deployment in production environments.
Ensure data privacy, security, and compliance with educational standards and regulations.
Document technical processes, model architectures, and evaluation results for internal and external stakeholders.
Stay curre

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired bya collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizationsunlock the value of technology and build a more sustainable, more inclusive world.

Location This is an onsite role to be based in either Chicago, IL or Seattle, WA or Grand Rapids, MI or Scottsdale, AZ or Atlanta, GA.

About the job you're considering We are seeking a passionate and innovative Software Development Engineer in Test (SDET) to join our Quality Engineering team and lead the development of LLM- and agentic-based testing solutions. This role blends traditional automation expertise with cutting-edge AI technologies to build intelligent, scalable, and autonomous testing frameworks that redefine how we validate software quality.

Your role Design and implement end-to-end testing frameworks leveraging Large Language Models (LLMs) and agentic workflows. Develop and maintain automated test suites for UI, API, and data layers across multiple platforms. Collaborate with AI/ML engineers to integrate Natural Language Processing (NLP) models into testing pipelines. Build and manage test data pipelines for diverse applications and environments. Create and maintain CI/CD pipelines to support continuous testing and deployment. Identify and resolve environmental and data dependencies for comprehensive E2E testing. Lead defect triage, backlog grooming, and root cause analysis sessions. Your skills and experience Around 1 year of experience working in or supporting AIbased testing environments, or strong interest with handson exposure through projects or coursework. Working knowledge of at least one programming or scripting langua

Role Name - Agentic AI Engineer

ROLE_DESCRIPTION -

AI Engineer Agentic Platforms & Autonomous Systems Location Flexible / Hybrid / Remote (based on business needs) Role Summary We are seeking an AI Engineer to design, build, and deploy intelligent agents using modern agentic AI platforms, including (but not limited to) Writer, Amazon Bedrock, UiPath, and similar frameworks. This role focuses on creating secure, governable, and scalable agents that can reason, plan, and act across enterprise workflows while integrating with business systems and data.

The ideal candidate is platform-agnostic, understands agent autonomy levels, and can design systems that balance automation, oversight, and trust.

Key Responsibilities Agent & AI System Development " Design and build AI agents capable of reasoning, planning, and executing tasks " Implement agents using multiple agentic platforms (Writer, Bedrock, UiPath, or equivalent) " Apply retrieval-augmented generation (RAG), tool invocation, and memory patterns " Define agent operating modes (assistive, workflow-driven, semi-autonomous) Key Responsibilities Platform Integration & Orchestration " Integrate agents with enterprise systems via APIs and automation frameworks " Connect agents to structured and unstructured data sources " Build orchestration logic separating planning, execution, and validation " Design reusable, cross-platform agent patterns Key Responsibilities Governance, Risk & Control " Implement human-in-the-loop, policy guardrails, and permission controls " Ensure agent actions are auditable, explainable, and compliant " Collaborate with security, risk, and compliance teams Evaluation & Optimization " Measure agent performance, accuracy, cost, and latency " Diagnose and mitigate agent failure modes " Continuously optimize prompts and orchestration logic Required Qualifications " 4+ years of experience in software, AI/ML, or automation engineering " Hands-on experience building LLM-powered agents or wo

AI Engineer – Agentic AI / LLM Systems

New York | Series A Startup

$180-$250k + Equity

In office ( 5 days)

No visa sponsorship available - OPT Visas will not be considered

A fast-growing, venture-backed AI company is hiring AI Engineers to help build systems where AI doesn’t just generate responses but executes real workflows.

The team is developing AI agents capable of reasoning, coordinating tools, and running multi-step operational processes across enterprise systems.

The role

Build and deploy agentic AI systems that automate complex workflowsDesign infrastructure for LLM orchestration, tool usage, and task executionDevelop production systems in PythonImplement RAG pipelines, multi-agent systems, and AI-driven automationWork closely with engineers and researchers pushing AI systems into production

Requirements

Strong engineering skills in PythonExperience with LLMs and building agentic frameworksExperience with LangChain, LangGraph, RAG, or similar orchestration toolsBackground in building scalable AI-powered applications or automation systems

This is an opportunity to join a small, highly technical team building next-generation AI systems backed by leading investors.

An Application Architect/Engineer specializing in Application Automation is responsible for designing and implementing automation solutions that streamline business processes and optimize service delivery. This individual understands functional and non-functional requirements and is able to provide solution architecture and design, technical leadership, perform technology evaluation and selection, performance optimization and take care of security and compliance requirements. This role involves working closely with stakeholders to understand business needs, architecting scalable automation solutions, and ensuring the integration of these solutions into the existing IT infrastructure for the client. An application architect must have expert level knowledge on automation tools and technologies (e.g., UiPath, Blue Prism, Automation Anywhere, AI/GenAI, Workflows), Assets (Digital Workers, IT/AI Operations, Agent Assistant etc.), APIs for Watsonx/ other hyperscalers. An Application Architect should also be acquainted with IDCP (*** delivery central platform) and *** Consulting Advantage platform consisting of Methodx, assets and assistants

HiHope you are doing well

This is Bhanu from Intellectt INC; we have an immediate opportunity with one of our clients. Please find the below job description and if you are interested, please forward your resume to bhanuprakash@intellectt.com

Position: Agentic AI Engineer (Python)
Location: Atlanta, GA – Onsite
Duration: Long Term

Job Description:

We are seeking an experienced Agentic AI Engineer to design and implement intelligent systems leveraging autonomous agents, LLMs, and advanced Python frameworks. The ideal candidate will have hands-on experience developing agentic AI solutions that can plan, reason, and act using multi-agent orchestration and modern AI toolkits.

Key Responsibilities:

Design and build agentic AI frameworks and intelligent workflows using LLMs.Develop and integrate Python-based AI applications with internal systems and APIs.Utilize tools such as LangChain, CrewAI, AutoGen, or OpenDevin for agent orchestration.Build AI pipelines that can autonomously perform reasoning, decision-making, and task execution.Collaborate with cross-functional teams to align AI initiatives with business goals.Optimize AI agents for scalability, performance, and accuracy in production environments.Stay current with advancements in LLMs, agentic AI, and generative AI ecosystems.Required Skills & Experience:

Strong programming skills in Python and familiarity with AI/ML frameworks.Proven experience developing LLM-driven or multi-agent AI systems.Hands-on experience with LangChain, AutoGen, CrewAI, or related frameworks.Knowledge of OpenAI, Anthropic, or AWS Bedrock APIs.Experience with prompt engineering, retrieval-augmented generation (RAG), and vector databases (e.g., FAISS, Pinecone, Chroma).Strong problem-solving and analytical skills.Excellent communication and teamwork abilities.Nice to Have:

Experience in healthcare or insurance domain.Familiarity with cloud platforms (AWS, Azure, or GCP) for deploying AI models.Exposure to MLOps or AI agent lifecycle ma

Build real AI systems—for real public impact.
Louisville Metro Government is seeking an Applied AI Engineering to serve as a hands-on builder and trusted technical advisor as we scale applied AI across city services.
This role blends modern AI engineering with strategic civic leadership. You will design, prototype, and integrate AI solutions while advising executive leadership on what is possible, what is risky, and what is worth scaling. You will help define Louisville Metro’s emerging AI platform, technical standards, and architectural patterns.
What You’ll Do

Partner with the CAIO, AI Product Lead, and departments to identify high-impact AI use cases.
Design and build AI solutions such as Q&A assistants, document intelligence, routing and triage tools, and workflow automations.
Serve as a technical advisor on AI capabilities, constraints, and risks.
Evaluate and integrate third-party AI platforms, ensuring compliance with security, data, and interoperability standards.
Collaborate with data, security, and infrastructure teams to define reusable technical patterns and reference architectures.
Design and execute experiments, proofs-of-concept, and pilot evaluations.
Communicate complex technical concepts in clear, accessible language to nontechnical stakeholders.
Develop and maintain technical documentation, runbooks, and operational handoffs.

Required Qualifications

Bachelor’s degree in Computer Science, Data Science, Engineering, Information Systems, or a related field.
Three (3) years of professional experience in software engineering, machine learning engineering, data engineering, or applied AI development (or equivalent experience).
Proficiency in Python and experience with modern AI/ML or LLM frameworks (e.g., PyTorch, TensorFlow, LangChain, LlamaIndex).
Experience building applied AI solutions such as chatbots, recommendation systems, document pipelines, and RAG architectures.
Experience with cloud platforms (AWS, Azure, or GCP), containerization, CI/C

Lead AI Engineer (AI Foundations, LLM Core and Agentic AI)

{"description": "Lead AI Engineer (AI Foundations, LLM Core and Agentic AI)

Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our cu

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It's why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It's why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it's why our business strategy centers on making journalism so good that it's worth paying for.

Department Overview:

Research & Development at The New York Times explores how emerging technologies can be applied in service of journalism. We collaborate with designers, developers, reporters, photographers and editors to bring new forms of storytelling to life, from prototyping to publishing.

At The Times, technology permeates every aspect of our business, from our thought-provoking coverage of technological trends to the digital-first transformation of our own business to the changing world of our readers. The Research & Development team explores the new opportunities that emerging technologies may provide the New York Times and our commercial and strategic goals.

We are looking for a Senior Software Engineer with a background in applied AI to develop applications using Large Language Models (LLMs) in service of The Times mission and journalistic standards. We are looking for someone who is comfortable building projects autonomously and enjoys collaboration with a larger team. You are both curious about and skeptical of emerging technologies, excited to apply new tools, but aim to do so in service of solving important problems and making a difference for users. You take pride in your craft and understand the need to capture patterns and support future development. This is a temporary position.

Responsibilities:
Design and implement LLM-backed APIs - driving improvements to reach target outcomes through evaluation, grounding and fine-tu

GPTZero is on a mission to restore trust and transparency on the internet. As the leading AI detection platform, we empower educators, students, journalists, marketers, and writers to navigate the evolving landscape of AI-generated content. With millions of users and institutions relying on us, we’re building a category-defining company at the intersection of AI and information integrity.

Our team comes from high-performing engineering cultures, including Meta, Perplexity, AWS, Affirm, and leading AI research labs, including Princeton, Caltech, and Vector Institute.

About this role:
In this role, you'll build the next generation of AI tools that preserve and enhance critical thinking for humanity. The ideal candidate is someone who is adept at creating reliable AI agents, prompt engineering, possesses a great product sense, and is also an excellent software engineer. You'll be working on a fast-paced team of passionate builders to create industry-defining software that has attracted millions of users globally.

What you'll contribute:


Fine-tune and evaluate state-of-the-art language models

Optimize prompts to maximize classification accuracy, personalize outputs, and enforce style guidelines

Develop multi-agent workflows incorporating data from diverse sources using RAG

Improve and iterate on AI agents using observability and experimentation tools

Stay up-to-date with the latest literature and emerging technologies to solve novel problems

Work closely with product and design teams to develop intuitive applications that create societal impact

Qualifications


3+ YOE in Python

1+ YOE in LLM framework like Langchain or LlamaIndex

1+ YOE with agentic or RAG applications

Strong exploratory data analysis (EDA) skills to effectively leverage data in a way that informs pragmatic solutions

Experience pushing the cutting-edge in LLM abilities on novel tasks with

GPTZero is on a mission to restore trust and transparency on the internet. As the leading AI detection platform, we empower educators, students, journalists, marketers, and writers to navigate the evolving landscape of AI-generated content. With millions of users and institutions relying on us, we’re building a category-defining company at the intersection of AI and information integrity.

Our team comes from high-performing engineering cultures, including Meta, Perplexity, AWS, Affirm, and leading AI research labs, including Princeton, Caltech, and Vector Institute.

About this role:In this role, you'll build the next generation of AI tools that preserve and enhance critical thinking for humanity. The ideal candidate is someone who is adept at creating reliable AI agents, prompt engineering, possesses a great product sense, and is also an excellent software engineer. You'll be working on a fast-paced team of passionate builders to create industry-defining software that has attracted millions of users globally.

What you'll contribute:Fine-tune and evaluate state-of-the-art language models

Optimize prompts to maximize classification accuracy, personalize outputs, and enforce style guidelines

Develop multi-agent workflows incorporating data from diverse sources using RAG

Improve and iterate on AI agents using observability and experimentation tools

Stay up-to-date with the latest literature and emerging technologies to solve novel problems

Work closely with product and design teams to develop intuitive applications that create societal impact

Qualifications3+ YOE in Python

1+ YOE in LLM framework like Langchain or LlamaIndex

1+ YOE with agentic or RAG applications

Strong exploratory data analysis (EDA) skills to effectively leverage data in a way that informs pragmatic solutions

Experience pushing the cutting-edge in LLM abilities on novel tasks with subjective outputs

Excellent software engineer with experience building highly extensible and modular

Job Description – Agentic AI Engineer (Fresher)

Company: Transnational AI Private Limited

Location: Coppell, TX (On-site )

Work Mode: onsite

About Transnational AI:

Transnational AI Private Limited is a Hyderabad-based global technology company building secure,

scalable, and intelligent agentic AI systems. Our AI platforms power digital exchanges across

employment, insurance, data, and financial services. We believe in creating real-world impact through

autonomous AI agents that plan, act, and learn responsibly. If you are passionate about building the future of intelligent systems — this is the place to grow your career.

Role Overview:

As a Fresher in the Agentic AI team, you will work on designing, developing, testing, and deploying

intelligent agent systems that interact with real users and platforms. You will get hands-on experience with cutting-edge LLM technologies, retrieval systems, tool integration, and agent orchestration frameworks — under strong mentorship from senior engineers. This is an excellent opportunity for

young engineers who want to build their careers at the intersection of AI, product, and systems

engineering.

Responsibilities:

• Contribute to building and maintaining agentic AI workflows — planning, decision-making,

orchestration.

• Work with LLMs, vector stores, prompt engineering, and RAG pipelines.

• Integrate agents with internal APIs, external tools, databases, and cloud services.

• Build guardrails, fallback strategies, and evaluation metrics for agent performance.

• Debug, monitor, and improve real-world AI agent behavior.

• Collaborate with AI, product, infrastructure, and domain teams to deliver production-ready solutions.

Qualifications:

• B.Tech / B.E. / M.Tech in Computer Science, AI, Data Science, or related fields.

• Strong programming skills (Python preferrhon preferred). • Basic understanding of ML / NLP / Generative AI.

• Familiarity with APIs, databases, and cloud tools.

• Strong

Job Number: R0233768

Agentic AI Engineer

The Opportunity:

We are looking for a highly skilled Agentic AI Engineer to join our team, specializing in building autonomous, goal-oriented AI systems. You will play a crucial role in shifting our AI strategy from passive LLM chatbots to proactive, multi-agent orchestrations. In this role, you will utilize deep experience in agent orchestration frameworks, RAG, knowledge graphs, and fine-tuning Small Language Models (SLMs) for edge deployment.

What You'll Work On:

Design and implement intelligent agent architectures that can reason, plan, and take actions using LangChain, LangGraph, and AutoGen.Develop and deploy multi-agent systems using MCP (Model Context Protocol) and A2A (Agent-to-Agent) protocols to facilitate communication, tool usage, and collaborative task solving.Build advanced RAG pipelines integrating unstructured data with Knowledge Graphs (KG) to enhance reasoning accuracy and context retention.Fine-tune Small Language Models (SLMs) for specific domains and optimize them for edge device performance, including ONNX, GGML, or Ollama.Develop evaluation frameworks to test agent reliability, safety, and performance, moving from prototype to production, including ReAct loops and human-in-the-loop.

Join us. The world can’t wait.

You Have:

5+ years of experience in software development2+ years of experience with GenAI, LLMs, and agentic workflowsExperience with LangChain, LangGraph, AutoGen, or LlamaIndexExperience with Model Context Protocol (MCP) for tool integration and A2A for agent-to-agent collaborationExperience in RAG architecture and Knowledge Graphs, including Neo4j or NebulaGraphExperience fine-tuning LLMs or SLMs using Hugging Face, PEFT, or LoRAKnowledge of modern software design patterns, including microservice design or edge computingAbility to obtain a Secret clearanceBachelor’s degree in a Computer Science or AI field

Nice If You Have:

Experience deploying agentic systems in a production en

Agentic AI Engineer

The Opportunity:
We are looking for a highly skilledAgentic AI Engineerto join our team, specializing in building autonomous, goal-oriented AI systems. You will play a crucial role in shifting our AI strategy from passive LLM chatbots to proactive, multi-agent orchestrations. In this role, you will utilize deep experience in agent orchestration frameworks, RAG, knowledge graphs, and fine-tuning Small Language Models (SLMs) for edge deployment.

What You'll Work On:

Design and implement intelligent agent architectures that can reason, plan, and take actions using LangChain, LangGraph, and AutoGen.

Develop and deploy multi-agent systems using MCP (Model Context Protocol) and A2A (Agent-to-Agent) protocols to facilitate communication, tool usage, and collaborative task solving.

Build advanced RAG pipelines integrating unstructured data with Knowledge Graphs (KG) to enhance reasoning accuracy and context retention.

Fine-tune Small Language Models (SLMs) for specific domains and optimize them for edge device performance, including ONNX, GGML, or Ollama.

Develop evaluation frameworks to test agent reliability, safety, and performance, moving from prototype to production, including ReAct loops and human-in-the-loop.

Join us. The world can't wait.

You Have:

5+ years of experience in software development

2+ years of experience with GenAI, LLMs, and agentic workflows

Experience withLangChain, LangGraph,AutoGen, orLlamaIndex

Experience withModel Context Protocol (MCP)for tool integration andA2Afor agent-to-agent collaboration

Experience inRAGarchitecture andKnowledge Graphs, including Neo4j or NebulaGraph

Experience fine-tuning LLMs or SLMs using Hugging Face, PEFT, or LoRA

Knowledge of modern software design patterns, including microservice design or edge computing

Ability to obtain a Secret clearance

Bachelor's degree in a Computer Science or AI field

Nice If You Have:

Experience deploying agentic systems in a production environme

A company is looking for a Senior ML / LLM Engineer to design and implement advanced AI systems for clinical applications.

Key Responsibilities

Design and implement AI Agents and build RAG pipelines based on clinical guidelines

Develop systems to synthesize clinical data into prioritized insights for clinicians

Ensure compliance with HIPAA and implement vector search infrastructure

Required Qualifications

Bachelor's degree preferred

5 years of experience in ML / LLM engineering with production-grade systems

Proficiency in vector databases and MLOps tools (Docker, Kubernetes)

Experience with C# / .NET for backend development

Familiarity with healthcare interoperability standards (FHIR, HL7) is a plus

LLM Engineer
12 month+ contract
100% Remote

Position Summary

Position Summary
The LLM Engineer is responsible for designing, developing, and deploying large language model solutions that support enterprise operations. This role focuses on Azure AI services, Azure OpenAI, and the integration of LLM capabilities into internal applications and workflows. The engineer will work closely with cross-functional teams to turn business requirements into scalable, production-ready AI solutions.

Key Responsibilities
• Design, develop, and deploy LLM-based applications using Azure AI, Azure OpenAI, and related cloud services
• Build retrieval-augmented generation (RAG) pipelines, embeddings, vector stores, and prompt workflows
• Integrate LLM capabilities into enterprise platforms such as Power Platform, Microsoft 365, and internal systems
• Prepare, clean, and transform data for LLM consumption and build feature and inference pipelines
• Implement model monitoring, lifecycle management, evaluations, and performance tuning
• Collaborate with automation engineers, product owners, and business stakeholders to assess and scope use cases
• Document solution architectures, model workflows, and technical designs
• Evaluate emerging AI tools, frameworks, and best practices
• Support troubleshooting, testing, and responsible AI standards

Required Skills and Experience
• Strong hands-on experience with Azure AI services, Azure OpenAI, or similar LLM platforms
• Proficiency in Python and common ML libraries (scikit-learn, pandas, PyTorch, TensorFlow)
• Practical experience building and deploying LLM applications, including embeddings, RAG, prompt engineering, and fine-tuning
• Understanding of data pipelines, model evaluation, and monitoring
• Experience integrating LLM solutions into enterprise systems
• Ability to communicate complex AI concepts clearly to both business and technical stakeholders

Preferred Experience
• Exposure to Power Platform AI Builder, Copilot Studio, or Micro

Company Description
Lumen Solutions Group Inc. is a technology consulting Services company based in Florida. We provide a wide array of experienced business and IT professionals supporting clients from solution design to implementation and support. We specialize in professional IT consulting services, IT Staffing, Business/IT Strategy, Business Process Blueprints, Enterprise Architecture, Enterprise Transformation.

Role: AI Agent Engineer / Agentic AI Engineer
Location: Austin, TX (Hybrid - On Site and Telework)
Job Type: Contract

Note: We need only Local Texas Candidates.

Job Summary:
We are seeking an experienced AI/ML Engineer / Autonomous Agent Engineer with 8+ years of hands-on experience in artificial intelligence, machine learning, and advanced data science to design, develop, and deploy production-grade autonomous AI agents and intelligent workflows. The ideal candidate will have a proven track record of building scalable, enterprise-ready AI solutions, including multi-agent systems, agentic workflows, and Retrieval-Augmented Generation (RAG) architectures using vector databases. This role requires deep expertise in context engineering, LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or AutoGPT, and strong proficiency in Python along with leading AI/ML libraries and platforms including OpenAI, Hugging Face, and Azure AI.

Required Skills

4+ years of experience in AI/ML engineering or advanced data science. 4+ years of proven track record of building and deploying production-grade autonomous agents. 4+ years of strong experience in context engineering. 4+ years of deep experience with LangChain, LangGraph, CrewAI, or AutoGPT. 4+ years of experience implementing RAG architectures using vector databases. 4+ years of proficiency in Python and AI/ML libraries (OpenAI, Hugging Face, Azure AI). 4+ years of experience integrating LLMs via APIs. 4+ years of knowledge of AI governance, model lifecycle management, and evaluation. 4+ years

We respectfully request that 3rd parties refrain from contacting us regarding this posting.

Overview

LABUR is partnering with a client executing a company-wide AI transformation across numerous initiatives spanning Finance, Sales, Marketing, Legal, RevOps, Product, HR, and Customer Experience. With a funded roadmap, enterprise AI licenses, and governed integrations already live, this role focuses on turning strategy into production-grade systems. We are seeking an Agentic AI Engineer to lead technical delivery, building agents, connectors, and workflows that unify CRM, ERP, HRIS, and data platforms into a natural-language-driven enterprise experience. This is a hands-on role centered on real-world delivery, reliability, and adoption.

Responsibilities

Design and build agentic systems that orchestrate across ERP, CRM, data warehouse, HRIS, and BI platforms.Develop multi-step AI workflows including tool selection, data retrieval, reasoning, and response generation.Build and extend enterprise integrations, including authentication (OAuth, SSO) and RBAC enforcement.Deliver AI-powered business solutions such as pricing engines, SDR automation, contract workflows, and executive dashboards.Implement governance frameworks including audit logging, data lineage, and PII protection.Partner with business teams to translate workflows into AI-enabled solutions.Drive adoption through reusable prompts, tools, and training for non-technical users.

Qualifications

3+ years of experience building API integrations with CRM, ERP, or HRIS platforms.Strong Python experience working with LLM APIs and SDKs.Hands-on experience with agentic architectures, including tool use, function calling, and multi-step workflows.Familiarity with AI frameworks such as LangChain, MCP, or similar.Experience implementing enterprise authentication, including OAuth, SSO/SAML, and role-based access control.Background working with data platforms, BI tools, and enterprise data governance concepts such as row-

Job DescriptionJoin a dynamic and fast-evolving team that is building next-generation AI-based tools and agent systems for the construction Industry. Our AI and Data Team is focused on designing intelligent AI agents and copilots using modern AI/ML techniques.

You will work closely with cross-functional teams, including business stakeholders, data engineers, and technical leads, to ensure alignment between business needs and data architecture and define data models for specific focus areas.

ResponsibilitiesBuild end-to-end Gen AI solutions - develop, refine, and implement advanced Gen AI models and ensure the successful delivery of projects.Develop and execute comprehensive plans to integrate AI technologies into business processes, aimed at enhancing operational efficiency and boosting employee productivity.Utilize Python and other data manipulation languages proficiently to prepare and manipulate data.Understand the business requirements and translate into Gen AI solution design that successfully meets the business objectives.Collaborate with stakeholders, present findings to non-technical audiences and provide strategic recommendations.Ensure the scalability, reliability, and security of AI solutions by implementing best practices for AI model development, deployment, and maintenance.Drive innovation by exploring new AI applications and solutions that can benefit the enterprise, leading research and development efforts to keep DPR at the forefront of AI technology.Follow the roadmap for AI initiatives, ensuring they align with organizational goals and show measurable impact.

QualificationsAt least 3 years of experience with Software Development, Machine Learning.At least 2 years of experience Generative AI, specifically with Large Language Models (LLM).Experience with generative AI concepts such as Retrieval-Augmented Generation (RAG), agentic workflows, training LLMs with structured and unstructured data sets.Experience with Data Connectors and API gateways

Miracle Software Systems, looking for a Generative AI Engineer to build cutting-edge AI applications powered by Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).

If you’re passionate about building scalable AI systems that combine enterprise data with modern cloud and APIs, this role is for you.

Required Skills:
• 8+ years of software engineering experience
• Strong Python expertise
• Hands-on experience with LLMs / Generative AI
• Experience building RAG systems
• Experience with vector databases (Pinecone, Weaviate, FAISS, etc.)
• Strong experience with FastAPI / REST APIs
• Solid knowledge of SQL & data processing
• Experience with GCP
• Familiarity with Git & Docker

What You’ll Do:
• Design and develop Generative AI applications using LLMs
• Build and optimize RAG pipelines using embeddings and vector databases
• Develop scalable REST APIs using FastAPI or similar frameworks
• Apply prompt engineering and model optimization techniques
• Build and manage data pipelines for AI systems
• Deploy solutions on Google Cloud Platform (GCP)
• Implement Docker-based deployments and CI/CD pipelines
• Collaborate with cross-functional teams to integrate AI into enterprise systems

Overview of Role As a Sr./Principal AI Engineer within TSMC's Artificial Intelligence for Business Intelligence Innovation (AI4BII) Center, you will join an exciting global team dedicated to generating crucial business intelligence insights that shape TSMC's strategic decisions and global operations. This role uniquely blends applied research with end-to-end product development, placing you at the forefront of our mission to leverage advanced AI for a competitive edge. Operating with the agility of an internal startup, you will have the autonomy to build foundational systems from the ground up. You will tackle complex challenges spanning from advanced analytics and multimodal AI agents to time-series forecasting and reinforcement learning for manufacturing optimization. This is a role for a builder and a researcher who has been through the "zero-to-one" product journey and thrives on rapid iteration, technical leadership, and seeing their work create tangible business impact. Our hybrid work schedule currently requires 4 days in the office, ensuring a dynamic and collaborative work environment. Responsibilities Lead System Architecture: Own the end-to-end design and development of new AI-native products and platforms, from initial concept and data pipelines to scalable, production-grade services. Build with Frontier AI: Drive the hands-on implementation of advanced AI systems leveraging frontier LLM models, including the design of robust Retrieval-Augmented Generation (RAG) pipelines and multi-agent workflows. Prototype and Validate: Lead rapid validation sprints to build proof-of-concepts, create evaluation harnesses to measure accuracy, latency, and cost, and partner with product teams to harden prototypes for production release. Engineer for Scale: Architect and implement the underlying MLOps infrastructure, including model serving, automated testing, and observability, to ensure our AI services meet enterprise-grade SLAs. Drive Innovation: Research and vali

What this role is

We build AI agents that do real work.

Not assistants. Not demos.

Agents that execute workflows end-to-end and produce correct outcomes.

Your job is to:
• build those agents
• and build the systems that make them reliable

This is not prompt engineering.

This is making AI work in production.

What you’ll do
• Build agents that execute multi-step workflows
• Design systems for validation, retry, and failure handling
• Define constraints (schemas, invariants, contracts)
• Add feedback loops (detect → debug → improve)
• Turn failures into reusable systems

What this role is NOT
• Not prompt engineering
• Not one-shot demos
• Not feature-heavy product work

You are building agents that do the work, and the systems that ensure they do it correctly.

Note: This is different from “vibe coding.” You won’t just prompt and accept outputs. You’ll build systems so results are reliable and repeatable.

What we’re looking for
• Strong systems thinking
• Background in:
• infrastructure, backend, or data systems
• developer tools or internal platforms
• Experience building reliable systems (not just features)
• Comfortable debugging complex, ambiguous problems

Important:

LLM experience alone is not enough.

We care about how you make systems reliable.

Good fit if you:
• Think in constraints, invariants, and feedback loops
• Care about correctness, not just output quality
• Have automated real workflows end-to-end
• Prefer building systems over features

Not a fit if you:
• Mostly prompt models and accept outputs
• Have only built demos or prototypes
• Avoid debugging or failure handling

Application (required)

1. Project (GitHub)

An agent system that:
• performs a multi-step task
• includes validation
• handles failures (retry, fallback, etc.)

2. Short answer (5–10 sentences)

Describe a system where an AI agent failed.

What caused it, and how would you fix it?

How we measure success
• Agents complete real workflows with minimal human input
• Outputs a

Agent Engineer (Agentic AI/LLM Systems)

Description -

Role Summary

Design and deliver agentic AI systems that operate across enterprise workflows. This role focuses on applied, system-level AI engineering rather than foundational model research or prompt-only experimentation

What You'll Do
• Design and implement agent-based systems using LLMs, tools, memory, and planning (including orchestration and multi-step workflows)
• Build and integrate agent workflows across enterprise systems via APIs and services with clear security, access control, and auditability boundaries
• Develop RAG pipelines where applicable to support agent reasoning
• Implement human-in-the-loop patterns for safety, review, escalation, and approval of high-impact actions.
• Define and operationalize evaluation frameworks (accuracy, reliability, task success)
• Own solutions from prototype through production deployment and monitoring and operational reliability
• Partner cross-functionally to deliver scalable, secure, and high-impact solutions

Qualifications

Required:
• Bachelor's or Master's in Computer Science, Data Science, or related field (or equivalent experience)
• Strong programming experience (Python required)
• Experience building LLM-based applications or workflow automation systems

Preferred:
• Experience with agent frameworks (e.g., LangChain, Semantic Kernel)
• Familiarity with RAG, vector databases, and evaluation techniques
• Experience designing multi-step or tool-augmented workflows

Core Competencies
• Agentic System Design
• Applied Generative AI
• Workflow Orchestration
• Evaluation & Reliability
• Software Engineering Excellence
• Cross-Functional Collaboration

The pay range for this role is $175,000 - $280,000 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience.

Benefits:

HP offers a comprehensive benefi

Junior LLM Engineer position in Norfolk, VA.
Average annual salary: $136,950.
Salary range: $102,713 to $198,578.
Required skills include Python, Transformers, Fine-tuning, RLHF, LangChain.
This is a full-time position with competitive compensation and benefits.

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired bya collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizationsunlock the value of technology and build a more sustainable, more inclusive world.
Location

This is an onsite role to be based in either Chicago, IL or Seattle, WA or Grand Rapids, MI or Scottsdale, AZ or Atlanta, GA.

About the job you're considering

We are seeking a passionate and innovative Software Development Engineer in Test (SDET) to join our Quality Engineering team and lead the development of LLM- and agentic-based testing solutions. This role blends traditional automation expertise with cutting-edge AI technologies to build intelligent, scalable, and autonomous testing frameworks that redefine how we validate software quality.

Your role
• Design and implement end-to-end testing frameworks leveraging Large Language Models (LLMs) and agentic workflows.
• Develop and maintain automated test suites for UI, API, and data layers across multiple platforms.
• Collaborate with AI/ML engineers to integrate Natural Language Processing (NLP) models into testing pipelines.
• Build and manage test data pipelines for diverse applications and environments.
• Create and maintain CI/CD pipelines to support continuous testing and deployment.
• Identify and resolve environmental and data dependencies for comprehensive E2E testing.
• Lead defect triage, backlog grooming, and root cause analysis sessions.

Your skills and experience
• Around 1 year of experience working in or supporting AIbased testing environments, or strong interest with handson exposure through projects or coursework.
• Working knowledge of at least one programming or scripting language such as Python (preferred), Java, or JavaScript.
• Basic to intermediate experience with test automation t

The Intuit T4I (Tech for Intuit) team is responsible for building Intuit's core capabilities supporting enterprise Workforce, People, and Places technologies. Our stakeholders include HR, Facilities, IT, segment business unit leaders, and all Intuit employees and expert workforce. The T4I engineering organization partners closely with product, design, and platform teams to deliver primarily internal services that improve productivity and employee experience across Intuit.

As a Staff ( Software | ML) Engineer, you will play a critical role in designing, building, and scaling AI-powered agents and copilots that support Intuit's workforce. This role is focused on applied AI systems, not research-delivering production-ready agent architectures that integrate with enterprise systems and workflows.

You will help define how and where AI agents add real value, making thoughtful tradeoffs between LLM-based approaches, traditional ML techniques, and simpler heuristic or rules-based solutions. You will work across backend services, AI platforms, and conversational interfaces to enable intelligent automation at scale.

This role is well suited for senior backend engineers with strong AI systems experience or ML engineers with strong software engineering foundations who are excited about building end-to-end agentic systems.

If you have a bias for action, enjoy operating in ambiguity, and are motivated by building practical AI solutions that drive measurable business impact, this role may be a great fit.

Responsibilities

ResponsibilitiesDesign and Build AI Agents: Architect, develop, and deploy AI agents and copilots that augment Intuit employees' workflows, integrating with internal systems and tools.
Own End-to-End AI Systems: Take solutions from concept to production-including model selection, prompt and context design, retrieval strategies, backend services, and conversational interfaces.Apply the Right Tool for the Problem: Evaluate business problems and determine w

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Ledgent Technology, is seeking the following. Apply via Dice today!

No Corp-to-corp / No Third-Party Agencies**We're Hiring on behalf of our client for Lead Agentic AI Engineer**
Hybrid Onsite near Fullerton, CA
190,000 to 210,000 annual salary (DOE)

*:**
Full-Time, Direct Hire
*Lead AI Developer - Microsoft/.NET Platform (On Prem)**
.
Partnered with a client who is seeking Lead AI Developer to help shape the next generation of intelligent, production-grade AI inside a mission critical, on prem manufacturing platform.

They're looking for a senior AI engineer who can own architecture, hands on development, and technical leadership as they embed advanced

*agentic**
capabilities, secure tool ecosystems, and reliable LLM integrations across Microsoft-based stack.
*What You'll DoArchitect end to end AI capabilities within an on prem .NET environment (ASP.NET, services, SQL Server).Build a robust agent runtime that handles tool execution, task state, routing, retries, and safe boundaries.Integrate with hosted LLM providers using modern tool/function-calling patterns and quality guardrails.Develop and maintain secure MCP-style tool servers for SQL, internal APIs, and file/report systems.Implement human in the loop controls, auditability, secrets management, and least privilege access patterns.Drive observability across logs, metrics, tracing, and dashboards.Establish testing strategies spanning unit, integration, failure simulation, and contract testing.Provide architectural direction, mentorship, reviews, documentation, and golden-path patterns for future AI dev work.Support deployments, troubleshooting, and alignment of AI capabilities with product priorities.What You Bring7+ years building distributed, production systems (Ideally, in .NET/C# services).2 years with agentic AI architecture/integration experience in business environment (not personal projects).Stron

No sponsorship available. No third-party/C2C candidates.

Applied AI Engineer, Senior or Mid-Level

Hybrid in just East Downtown Austin, TX Only - 2 days on-site, 3 Remote

This is an exclusive, off-market opportunity. Our executive client searches are confidential. Apply now to learn more about this unique new position!

We are seeking an Applied AI Engineer to join our dynamic team. As a leader in AI-driven solutions.

We specialize in building realworld AI applications that empower businesses.

In this role, you will design, implement, AIpowered applications and workflows while collaborating with cross-functional teams in a fast-paced, Agile environment.

Responsibilities
• Design, develop, and deploy AI-powered applications, data processing pipelines, chatbots, and intelligent automation tools using state-of-the-art AI models on AWS cloud infrastructure.
• Build and maintain robust backend systems using Python, with a focus on FastAPI frameworks.
• Optimize AI model inference and integrate large language models (LLMs) into scalable production environments.
• Leverage frameworks like LangChain and LangGraph to develop innovative AI solutions.

Qualifications
• 3+ years of experience as a full-stack software developer
• Exposure or recent experience with LLM projects or software professionally or at a freelance level
• Strong API development experience, including integrating AI models into production systems.
• Python development, with hands-on experience using FastAPI is a plus
• Experience with TypeScript Node.js and React.js is a must (Next.js is a plus)
• Familiarity AI frameworks such as LangChain and LangGraph is highly desirable.

Bonus Perks

As a valuable new member of the team, you will have access to a collaborative and innovative work environment, opportunities to expand your AI expertise, and the support of a highly skilled technical team.

Want to find out more about this job opportunity? Apply now!

Paradigm is a software company transforming the way that the residential construction & building product industries operate across the globe. We are looking for a Senior Applied AI Engineer to be part of revolutionizing these industries.

The Senior Applied AI Engineer will design, deploy, and optimize AI systems that power next-generation construction workflows. In this role, you’ll build the bridge between machine learning models and real-world applications—using LLMs, computer vision, retrieval systems, and agentic orchestration to automate key steps in the homebuilding process such as plan interpretation, takeoffs, estimating, and specification matching.

This role blends hands-on engineering, AI system design, and integration with enterprise platforms—turning AI capabilities into production-ready features that builders, designers, and estimators can rely on daily.

What You Will Do:
• Build and deploy advanced agentic AI systems that combine large language models, computer vision, and rules-based logic to automate construction workflows.
• Implement and optimize retrieval-augmented generation (RAG) pipelines to connect LLMs with real-time project data, specifications, and plan sets.
• Integrate AI models into production services and APIs for use in design, estimating, and procurement applications.
• Fine-tune and adapt pre-trained models for domain-specific tasks such as plan understanding, entity extraction, and bill-of-material generation.
• Evaluate and refine model accuracy, reasoning quality, and cost efficiency through Evals, zero/few-shot tests, Chain-of-Thought reasoning analysis, and LLM-as-a-judge evaluation techniques.
• Optimize inference performance and ensure system reliability in live environments.
• Work closely with data engineers to structure, index, and prepare complex multimodal datasets (text, CAD/BIM files, images) for AI consumption.
• Implement and refine robust data pipelines for training, validation, and feedback loops to continuously

About Fractional AI

Fractional AI builds bespoke software to help organizations solve complex, high-impact problems.

Every C-suite in the country is trying to bridge the gap between AI in theory and AI in practice. We close this gap with exceptional engineering talent and custom end-to-end AI builds (see some of our case studies to learn more).

By joining Fractional AI, you’re stepping onto a San Francisco, NYC, NC, and Dubai-based team working on AI projects for top companies from the comfort of an engineering-first startup.

Fractional AI is launching a new enterprise division, which is physically headquartered in the Triangle of North Carolina. The enterprise division is initially focused on healthcare and life sciences (an area where our leadership team has deep experience), with plans to expand into other industries as we grow. This unique opportunity allows you to be a part of the founding team to help build the division from scratch, but with the stability and resources of an established and profitable startup.

About the Role

Joining Fractional AI as a Forward-Deployed AI Engineer, you’ll play a leading role in building and shipping AI applications for our customers - from understanding customer needs to deploying solutions in their environments - all while shaping our engineering and broader Fractional culture for the next 100+ engineers.

“Forward-deployed” means we combine software engineering with customer-facing problem solving, owning delivery from early scoping through deployment and iteration. You’ll spend most of your time coding, but close enough to customers to shape the right solution end-to-end.

By the time you’ve completed your second project, you’ll have shipped LLM applications across more companies and use cases than the vast majority of AI engineers in the world.

What you bring to the table
• You write exceptional code + deeply care about the craft of coding (5+ years of experience): you build elegant, production-ready code; you have

Company: Qualcomm Technologies, Inc.

Job Area: Engineering Group, Engineering Group > Machine Learning Engineering

General Summary:

LLM Serving Engineer (Cloud AI Engineering )

Qualcomm is utilizing its traditional strengths in digital wireless technologies to play a central role in the evolution of Cloud AI. We are investing in several supporting technologies including Deep Learning. The Qualcomm Cloud AI team is developing hardware and software solutions for Inference Acceleration.

We are hiring LLM Serving Engineers at multiple levels to join our dynamic, collaborative team. This role spans the full product lifecycle—from cutting-edge research and development to commercial deployment—and demands strategic thinking, strong execution, and excellent communication skills.

This role involve s the following activities:

Building a scalable LLM inference platform using inference techniques ( e.g. disaggregated serving and KV - C ache management , advanced parallelism, speculative algorithms , model optimization , specialized kernels ) .

Contribute to the development of LLM Serving packages ( e.g. vLLM , SGLang , TGI, Triton -Inferen ce server , D ynamo, LLM-d ) .

Work closely with customers to drive solutions by collaborating with internal compiler, firmware and platform teams.

Work at the fore front of Gen AI by understanding advanced algorithms ( e.g. attention mechanisms, MoEs ) and numerics to identify new optimization opportunities .

Drive efficient serving through smart autoscaling, load balancing and routing .

Engage with open - source serving communities to evolve the framework .

Candidates for this position will demonstrate the following :

Hands-on e xperience in one or more of the following LLM serving /Orchestration packages ( Triton

Luminary helps engineering companies be more competitive by getting to market faster, creating new, better products, and reducing development risk. We do this with our Physics AI platform, the fastest and easiest way to build and deploy models to understand and instantly predict physical reality with precision. Customers span industries from automotive and aerospace, to leading sporting equipment providers, including Otto Aviation, Joby Aviation, Piper Aircraft and Trek Bikes. Luminary is a Series B company and is headquartered in San Mateo, California.

About LuminaryLuminary helps engineering companies be more competitive by getting to market faster, creating new, better products, and reducing development risk. We do this with our Physics AI platform, the fastest and easiest way to build and deploy models to understand and instantly predict physical reality with precision. Customers span industries from automotive and aerospace, to leading sporting equipment providers, including Otto Aviation, Joby Aviation, Piper Aircraft and Trek Bikes. Luminary is a Series B company and is headquartered in San Mateo, California.

The RoleWe're looking for an LLM Engineer to architect our Physics AI Copilot—the next generation of intelligent assistants for engineering workflows. You'll work at the intersection of large language models and domain-specific engineering challenges, creating AI experiences that dramatically accelerate how engineers work.

ResponsibilitiesDevelop Agentic AI systems: Design and implement tools for agents to call; build reasoning, planning, and orchestration capabilities that enable the copilot to autonomously execute complex engineering workflows

Design and optimize RAG pipelines: Build retrieval-augmented generation systems over engineering documentation, physics simulation results, and domain knowledge bases

Implement memory and context management: Create persistent conversation memory and context systems that maintain coherent, l

A leading technology company is seeking a Senior AI and LLM Engineer to innovate and integrate advanced AI solutions into their workflows. The ideal candidate will have an MS in a related field, over 8 years of experience, and strong skills in Python and AI frameworks. You will collaborate with engineering teams and design AI systems to enhance efficiency. The role offers a competitive salary range of $184,000 - $287,500 based on experience and location, with remote and hybrid work options. #J-18808-Ljbffr

About Lyzr

Lyzr is a Series A–backed enterprise AI company building a full-stack agent infrastructure platform that helps organizations design, deploy, and govern AI agents. Our platform enables enterprises to move beyond isolated AI use cases and into reliable, production-grade agentic workflows with strong controls around security, accuracy, and compliance.

Recognized by Accenture and Harvard Business School–led innovation ecosystems, Lyzr works with global enterprises to reimagine complex workflows using agentic AI. We focus on making AI agents dependable at scale - so teams can replace fragmented tool stacks with a unified, governed intelligence layer.

About The Job

You won't just be building interfaces; you will be architecting the future of work. You’ll be at the forefront of the "Third Way" of enterprise AI—combining open-source flexibility with enterprise-grade security. You will build Agentic apps on Lyzr, solving complex client requirements by turning fragmented processes into autonomous, intelligent workflows.

What You’ll Do

Build & Orchestrate: Design and deploy sophisticated AI Agents using the Lyzr Agent Studio and SDKs.

Full-Stack Ownership: Develop end-to-end applications with a heavy focus on Python backends and React frontends.

Client Success: Work closely with enterprise clients to translate business requirements into high-performing agentic architectures.

AI Innovation: Implement multi-agent collaboration, memory systems, and RAG-driven orchestrations.

What You Bring

Experience: 4+ years of professional full-stack development.

Tech Stack: Deep proficiency in Python (FastAPI/Django) and React.js.

AI-Native Workflow: You don’t just use a terminal; you leverage Cursor, Claude Code, and other LLM-powered coding tools to ship 10x faster.

LLM Fluency: Familiarity with LLM orchestration, prompt engineering, and the agentic AI landscape.

Location: Based in or willing to work in New York (This is an immediate, onsite/hybrid position).

Why

Role: AI Agent Developer / Agentic AI Developer

Local to MN candidates (Onsite )

Role Summary

Design, build, and scale autonomous AI agents that augment software engineering, DevSecOps, and enterprise developer workflows using modern large language models (LLMs) and agentic architectures.

Key Responsibilities

Design and develop autonomous and semi autonomous AI agents leveraging LLMs and agentic frameworks to solve complex engineering and operational problems.

Build AI-powered developer productivity tools, including assistants for code generation, review, refactoring, and documentation.

Develop and deploy agents that automate coding, testing, CI/CD, DevSecOps, and quality assurance workflows.

Integrate leading LLM platforms and copilots (e.g., GitHub Copilot, Claude, Codex) into enterprise developer toolchains and workflows.

Architect agent orchestration, tool calling, memory, and feedback loops to ensure reliability, security, and scalability.

Partner with platform, security, and engineering teams to ensure secure, compliant, and production ready AI solutions.

Continuously evaluate emerging LLMs, frameworks, and agentic patterns to drive innovation and best practices.

Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration)

{"description": "Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration)

Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates wor

• *About xAI**

xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge.

Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity.

We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important.

All engineers and researchers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.

About the Role

Forward Deployed AI Engineers work directly with our end customers owning strategy and execution.

Your responsibilities look similar to that of a hands-on AI startup CTO: you’ll work in a small team to own delivery of high stakes projects with clients. A day’s work may include:
• Deliver solutions end to end that meet the needs of our customers - understanding user pain points, scoping product specs, and designing and building LLM-powered software
• Benchmarking the model or help write evals for customers to identify model weaknesses
• Improve model performance by system prompt tuning or fine tuning models
• Analyze request logs or read through prompt data
• Build internal tooling to automate yourself out of the job
• Improving xAI SDKs or developer documentation based on customer feedback

Focus
• Strong passion for solving real-world business problems and delivering measurable impact through AI solutions.
• Proven track record of shipping high-quality code and successfully completing projects in challenging environments.
• Ability to navigate ambiguity and adapt to changing requirements and priorities in a fast-paced startup environment.
• Strong communication skills that will become

Key Responsibilities Develop and maintain backend services using Core Java and Spring Boot. Integrate AI/LLM workflows into Java applications using frameworks like Spring AI. Design and consume RESTful APIs; familiarity with SOAP/WSDL/XML is a plus. Build and support event-driven systems using Kafka, JMS, and other messaging platforms. Collaborate on frontend development using frameworks such as React, Angular, or Vue. Implement observability tools for logging, metrics, and tracing. Contribute to CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes). Apply clean architecture principles and design patterns in system design. Participate in technical discussions, mentor team members, and collaborate across teams. Skill Metrics Restful APIs Docker Kubernetes Ai/LLM Java Spring Boot Required Skills 7–10+ years of experience in Java development and Spring ecosystem. Experience with AI/LLM integration in Java applications. Strong knowledge of REST APIs and event-driven architecture. Familiarity with frontend frameworks and responsive design. Experience with observability tools (Logback, Prometheus, OpenTelemetry). Proficiency in CI/CD, Docker, Kubernetes, and version control systems. Solid understanding of software design principles and architecture. Preferred Qualifications Experience with Spring Cloud and microservices components. Familiarity with vector databases (Pinecone, Milvus, Redis vector). Knowledge of domain-driven design, CQRS, and reactive programming (Spring WebFlux). Understanding of OAuth, JWT, and enterprise security protocols. Exposure to cloud-native AI deployments (AWS Lambda, Azure AI, Google Vertex AI). Experience with legacy system modernization and hybrid deployments. Knowledge of AI orchestration, prompt chaining, and multi-agent workflows. Experience with feature toggles, A/B testing, and canary deployments. Seniority level Mid-Senior level Employment type Contract Job function Engineering and Information Technology Industr

Outstanding long-term contract opportunity! A well-known Financial Services Company is looking for a Senior Python LLM Engineer (W2) in Charlotte, NC Irving TX, Chandler/Phoenix AZ (Hybrid).

Work with the brightest minds at one of the largest financial institutions in the world. This is a long-term contract opportunity that includes a competitive benefit package! Our client has been around for over 150 years and is continuously innovating in today's digital age. If you want to work for a company that is not only a household name, but also truly cares about satisfying customers' financial needs and helping people succeed financially, apply today.

Contract Duration: 12 +Months

We are seeking a contract Senior Python LLM Engineer to improve and modernize IT Operations practices across Azure, GCP, and OpenShift environments. This role will act as a hands-on operational leader and change agent, driving simplification, standardization, and improved service stability within a large-scale enterprise.

The contractor will support operational transformation efforts, facilitate major incident management, validate operational readiness, and remediate process gaps across hybrid cloud platforms.

Key Responsibilities

• Serve as a catalyst to improve IT Operations practices, migrating legacy support models to standardized, simplified frameworks.

• Define operational processes and drive adoption of enterprise best practices.

• Facilitate major incident management calls across Azure, GCP, and OpenShift environments.

• Lead post-incident reviews and ensure corrective actions are implemented.

• Deliver Operational Readiness Reviews (ORR) and assessment artifacts.

• Validate operational controls, monitoring, alerting, and support readiness prior to production release.

• Identify operational deviations and drive remediation efforts.

• Develop Python-based automation and LLM-enabled tooling to enhance operational efficiency and diagnostics.

• Partner cross-functionally

About the position

We are seeking an experienced LLM Engineer to join our client's newly established LLM Ops Team in their Raleigh, NC office. In this role, you will be responsible for managing the complex lifecycle of Large Language Models from development to deployment, monitoring, and continuous improvement.\n\nThis role is hybrid to the Raleigh, NC area.

Responsibilities

Fine-tune pre-trained models for specific use casesCurate and prepare datasets for trainingManage training infrastructure, resources, and computational environmentsImplement optimization techniques to improve model performanceDevelop and manage APIs for model servingScale infrastructure to handle varying demand loadsBuild and maintain the GenAI middleware/sidecar layerIntegrate LLMs with existing systems and data sourcesTrack performance metrics including latency and throughputMonitor quality metrics such as hallucination rates and accuracyOptimize costs associated with model inference and trainingCreate and maintain dashboards for real-time performance insightsCreate and maintain golden datasets for benchmark testingImplement statistical validation methods for model outputsSet up similarity matching criteria for response evaluationDevelop confidence score thresholds for production systemsDesign and implement user feedback collection systemsEstablish continuous improvement processesCreate A/B testing frameworks for model and feature evaluationConduct trace analysis to identify areas for performance optimizationImplement content moderation systemsDetect and mitigate bias in model outputsEnsure regulatory compliance in AI systemsDevelop output validation frameworksVersion and store prompts systematicallyCreate and maintain prompt templatesSet up playground environments for prompt testingAbstract prompts from application code for better maintainabilityRequirements

Experience with LLM development, fine-tuning, and deploymentStrong programming skills, particularly in PythonExperience with Kubeflo

About Tribe AI:

At Tribe, we’re on a mission to help enterprises rearchitect their business with AI. Today, every large enterprise wants to transform its business with AI, but they often lack the capabilities to do so. At Tribe, this gap is our opportunity.

We embed senior engineers to design, ship, and operate AI systems where correctness is probabilistic, failure modes are subtle, and success is measured by adoption, stability, and business outcomes.

About the Role

This is a forward-deployed, hands-on engineering role for people who’ve lived through multiple technology waves and know the difference between what’s exciting and what survives production.

You’ll embed with enterprise teams to build and harden LLM-powered systems under real constraints: hallucinations, retrieval failures, agent misbehavior, silent regressions, cost explosions, and shifting data distributions. You own systems end-to-end, from architecture through post-launch behavior.

This is not a research role, a prompt-only role, or a feature factory.

It is a delivery role for engineers who can make stochastic systems behave well enough that businesses rely on them.

‍

Examples of what You’ll Own:

Own production AI systems end-to-end
• Design, build, deploy, and operate LLM-powered systems in production.
• Own reliability for probabilistic systems: hallucinations, grounding, drift, latency, and cost.
• Make tradeoffs explicit when correctness, speed, and cost are in tension.

LLM, RAG, and/or Agentic Systems experience
• Build and debug RAG pipelines: ingestion, chunking, retrieval quality, reranking, grounding, and evaluation.
• Design agent workflows that interact with tools, APIs, and data without looping, stalling, or hallucinating authority.
• Identify when agents are the wrong abstraction and kill them early.

Evaluation, Observability, and Drift
• Build and maintain evaluation frameworks for LLM outputs (offline, online, human-in-the-loop).
• Detect silent regressions caused by model

Role: AI Agent Engineer

Location: Austin TX

Duration: 4 Contract

Job Description

HHSC has issued a request for an AI Agent Engineer that will be responsible for designing and building agentic AI solutions, including autonomous workflows and RAG-based systems, to improve productivity, automate business processes, and support intelligent decision-making. This role focuses on production-grade agent development using tools like LangChain, LangGraph, CrewAI, and AutoGPT, with strong attention to governance, security, safety controls, and cost efficiency. The ideal candidate brings strong Python and LLM integration experience, plus the ability to build secure, scalable AI solutions for enterprise use.

Responsibilities include (but are not limited to):

Design and develop autonomous AI agents, RAG pipelines, and intelligent workflows that support business automation and decision-making.
Integrate LLMs securely using APIs, vector databases, MCP, and AI guardrails to support governed enterprise use cases.
Build, test, and maintain production-ready AI solutions with strong focus on governance, privacy, safety, and cost efficiency.

Minimum Candidate Characteristics:

4+ years of experience in AI/ML engineering or advanced data science with proven delivery of production-grade autonomous agents.
4+ years of experience building RAG architectures using vector databases and integrating LLMs through APIs.
4+ years of hands-on experience with Python, AI/ML libraries, and agent frameworks such as LangChain, LangGraph, CrewAI, or AutoGPT.

Exceptional Candidate Characteristics:

Experience with an HHS agency.
Experience building multi-agent or autonomous agentic workflows in enterprise environments.
Experience optimizing LLM cost, token usage, and runtime performance.
Familiarity with enterprise AI deployment patterns, scalability, and operational controls.

Pay: $70.00 - $75.00 per hour

Benefits:

401(k)
Dental insurance
Health insurance
Vision insur

Senior Lead AI Engineer (LLM Customization and Finetuning)

Overview:

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:
• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
• Design, develop, test, deploy, and support AI software components includin

Job Description

Join the Legal Tech Revolution at Litera
Are you ready to shape the future of how law is practiced? At Litera, we’re on a mission to Raise The Bar™️ for the legal profession by delivering transformational and globally-trusted solutions to law firms and corporate legal teams worldwide. We’ve been a leader in legal tech innovation for 30 years and are leading the legal AI revolution to this day with most of the world’s largest law firms as our clients. If you’re passionate about building AI-forward solutions that scale globally and want your work to impact millions of legal professionals worldwide, this is your opportunity to be part of an extraordinary team that’s elevating the craft of law.

This position is based in Denver, Colorado or Raleigh, NC and candidates should reside within reasonable commuting distance, as this role requires on-site presence at least three days per week.

About the Role
We are seeking an experienced LLM Engineer to join our newly established LLM Ops Team. In this role, you will be responsible for managing the complex lifecycle of Large Language Models from development to deployment, monitoring, and continuous improvement.

Key Responsibilities:
Model Development & Training
• Fine-tune pre-trained models for specific use cases
• Curate and prepare datasets for training
• Manage training infrastructure, resources, and computational environments
• Implement optimization techniques to improve model performance

Deployment & Serving
• Develop and manage APIs for model serving
• Scale infrastructure to handle varying demand loads
• Build and maintain the GenAI middleware/sidecar layer
• Integrate LLMs with existing systems and data sources

Monitoring & Evaluation
• Track performance metrics including latency and throughput
• Monitor quality metrics such as hallucination rates and accuracy
• Optimize costs associated with model inference and training
• Create and maintain dashboards for real-time performance insights

Testing &

The Intuit T4I (Tech for Intuit) team is responsible for building Intuit’s core capabilities supporting enterprise Workforce, People, and Places technologies. Our stakeholders include HR, Facilities, IT, segment business unit leaders, and all Intuit employees and expert workforce. The T4I engineering organization partners closely with product, design, and platform teams to deliver primarily internal services that improve productivity and employee experience across Intuit.

As a Staff ( Software | ML) Engineer, you will play a critical role in designing, building, and scaling AI-powered agents and copilots that support Intuit’s workforce. This role is focused on applied AI systems, not research—delivering production-ready agent architectures that integrate with enterprise systems and workflows.

You will help define how and where AI agents add real value, making thoughtful tradeoffs between LLM-based approaches, traditional ML techniques, and simpler heuristic or rules-based solutions. You will work across backend services, AI platforms, and conversational interfaces to enable intelligent automation at scale.

This role is well suited for senior backend engineers with strong AI systems experience or ML engineers with strong software engineering foundations who are excited about building end-to-end agentic systems.

If you have a bias for action, enjoy operating in ambiguity, and are motivated by building practical AI solutions that drive measurable business impact, this role may be a great fit.

Responsibilities

ResponsibilitiesDesign and Build AI Agents: Architect, develop, and deploy AI agents and copilots that augment Intuit employees’ workflows, integrating with internal systems and tools.
Own End-to-End AI Systems: Take solutions from concept to production—including model selection, prompt and context design, retrieval strategies, backend services, and conversational interfaces.Apply the Right Tool for the Problem: Evaluate business problems and determine w

GAP INTERNATIONAL – A unique, purpose-driven, consulting company

ABOUT GAP INTERNATIONAL

Gap International is a global consulting firm that partners with executives to achieve breakthrough business results. We're a team of passionate problem-solvers committed to innovation and transformation. As part of our growth strategy, we're expanding our AI capabilities to deliver cutting-edge solutions across the enterprise. This role offers the opportunity to work on impactful projects, including dialog-driven learning and business process acceleration.

ABOUT THE ROLE

You will be part of a tight knit, highly collaborative research and development team focused on building real-world AI applications. As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on large language models and natural language understanding. Your work will involve techniques such as fine-tuning, retrieval-augmented generation (RAG), and prompt engineering to solve meaningful business challenges.

You will work closely with teams to explore data, shape requirements, and integrate AI capabilities into internal tools and digital products. Your contributions will drive innovation and shape transformative projects across the organization.

RESPONSIBILITIES

Design and implement AI systems using Large Language Models (LLMs) to solve enterprise challenges and improve operational efficiency.
Fine-tune foundation models and apply techniques such as retrieval-augmented generation (RAG) and prompt engineering.
Collaborate with cross-functional teams to integrate AI capabilities into internal tools, workflows, and digital products.
Evaluate and experiment with frameworks and tools like Hugging Face, LangChain, OpenAI, Claude, and LLaMA.
Build and deploy scalable LLM solutions across cloud-based and local environments, leveraging container orchestration tools where applicable.
Lead architectural decisions and guide implementation o

#WeAreIn to create tiny chips and big careers. Are you ready to take the first step of your career? Let's shape the future together! Whether you join as a student, intern or trainee, you'll be part of something real - real projects, real impact, and real opportunities to grow. Are you in?

Your Role

Key responsibilities in your new role
• Agentic AI Development: Build agentic AI tools to enhance software and firmware development workflows\
• Data Mining: Analyze and extract insights from configuration data stored in data lake repositories
• LLM/SLM Tools: Develop application-level large/small language models for device configuration automation
• Machine Learning/NLP: Leverage ML and NLP algorithms to solve real-world engineering problems
• Database Expertise: Utilize SQL/NoSQL databases for data storage, access, and analysis
• Programming Languages: Apply Python, JavaScript, and other tools for AI and software development tasks

Your Profile

Qualifications and skills to help you succeed
• Education: Pursuing Bachelor’s or Master’s in Computer Science, Electrical Engineering, or Data Science
• Programming Languages: Proficiency in Python, JavaScript/TypeScript, or MATLAB
• AI Frameworks: Familiarity with tools such as Hugging Face or LangChain for LLM/SLM development
• Multidisciplinary Focus: Interest in embedded systems, power electronics, or configuration workflows
• Database Knowledge: Experience with SQL/NoSQL databases and data analysis workflows
• Collaboration Skills: Strong communication skills for teamwork and agile development environments
• Find out what we are looking for in your CV
• Find out how the student application process works with us
• Discover our student website

#WeAreIn for driving decarbonization and digitalization.
As a global leader in semiconductor solutions in power systems and IoT, Infineon enables game-changing solutions for green and efficient energy, clean and safe mobility, as well as smart and secure IoT. Together, we drive inno

Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration)

Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

Design, develop, test, deploy, and support A

POSITION
LLM Engineer

LOCATION
Hybrid - Chicago, IL, New York City, NY, Princeton, NJ

DURATION
Contract

PAY RATE
$52.7/hour W2

INTERVIEW TYPE
Video

VISA RESTRICTIONS
None

REQUIRED SKILLS
• Experience implementing RAG and have just used managed stack, and LLM APIs
• Endpoint building chatbot using documents and enterprise data or building action models
• Python experience
• Cloud platforms (AWS, Azure, GCP), and DevOps tools

About the Company:
Syntricate Technologies Inc

Chicago, Atlanta, Bridgewater, Southfield

AI/LLM Engineer

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Location

This is an onsite role to be based in either Chicago, IL or Seattle, WA or Grand Rapids, MI or Scottsdale, AZ or Atlanta, GA.

About the job you’re considering

We are seeking a passionate and innovative Software Development Engineer in Test (SDET) to join our Quality Engineering team and lead the development of LLM- and agentic-based testing solutions. This role blends traditional automation expertise with cutting-edge AI technologies to build intelligent, scalable, and autonomous testing frameworks that redefine how we validate software quality.

Your role
• Design and implement end-to-end testing frameworks leveraging Large Language Models (LLMs) and agentic workflows.
• Develop and maintain automated test suites for UI, API, and data layers across multiple platforms.
• Collaborate with AI/ML engineers to integrate Natural Language Processing (NLP) models into testing pipelines.
• Build and manage test data pipelines for diverse applications and environments.
• Create and maintain CI/CD pipelines to support continuous testing and deployment.
• Identify and resolve environmental and data dependencies for comprehensive E2E testing.
• Lead defect triage, backlog grooming, and root cause analysis sessions.

Your skills and experience
• Around 1 year of experience working in or supporting AI‑based testing environments, or strong interest with hands‑on exposure through projects or coursework.
• Working knowledge of at least one programming or scripting language such as Python (preferred), Java, or Java

Agentic AI Engineer

The Opportunity:
We are looking for a highly skilled Agentic AI Engineer to join our team, specializing in building autonomous, goal-oriented AI systems. You will play a crucial role in shifting our AI strategy from passive LLM chatbots to proactive, multi-agent orchestrations. In this role, you will utilize deep experience in agent orchestration frameworks, RAG, knowledge graphs, and fine-tuning Small Language Models (SLMs) for edge deployment.

What You'll Work On:
• Design and implement intelligent agent architectures that can reason, plan, and take actions using LangChain, LangGraph, and AutoGen.
• Develop and deploy multi-agent systems using MCP (Model Context Protocol) and A2A (Agent-to-Agent) protocols to facilitate communication, tool usage, and collaborative task solving.
• Build advanced RAG pipelines integrating unstructured data with Knowledge Graphs (KG) to enhance reasoning accuracy and context retention.
• Fine-tune Small Language Models (SLMs) for specific domains and optimize them for edge device performance, including ONNX, GGML, or Ollama.
• Develop evaluation frameworks to test agent reliability, safety, and performance, moving from prototype to production, including ReAct loops and human-in-the-loop.

Join us. The world can’t wait.

You Have:
• 5+ years of experience in software development
• 2+ years of experience with GenAI, LLMs, and agentic workflows
• Experience with LangChain, LangGraph, AutoGen, or LlamaIndex
• Experience with Model Context Protocol (MCP) for tool integration and A2A for agent-to-agent collaboration
• Experience in RAG architecture and Knowledge Graphs, including Neo4j or NebulaGraph
• Experience fine-tuning LLMs or SLMs using Hugging Face, PEFT, or LoRA
• Knowledge of modern software design patterns, including microservice design or edge computing
• Ability to obtain a Secret clearance
• Bachelor’s degree in a Computer Science or AI field

Nice If You Have:
• Experience deploying agentic systems in a

Dice is the leading career destination for tech experts at every stage of their careers. Our client, K Anand Corporation, is seeking the following. Apply via Dice today!

AI Developer / Agentic AI Engineer

Role Summary

We are building an agentic AI platform to transform commercial banking customer service. The AI developer will design, build, and operate LLM-powered agents that interpret inbound servicing requests (e.g., email / case intake), retrieve grounded knowledge, and execute approved workflows through secure tool/API integrations with enterprise-grade controls, observability, and human-in-the-loop patterns.

This role sits within a cross-functional team with Product, Operations, Technology, and Risk partners and focuses on delivering production-ready agentic AI capabilities for regulated financial services

Responsibilities

Agentic AI Solution Development
• Build and enhance LLM/agent orchestration (Planner/supervisor patterns, tool-using agents, routing, guardrails).
• Implement intent classification information extraction validation and decision logic for servicing workflows
• Developed tool calling integrations to downstream systems (CRM, workflow engine, core banking services, case management)
• Implement human-in-the-loop workflows (review, approval, escalation, override) based on confidence/risk thresholds

Knowledge and grounding (RAG)
• Design and implement retrieval-augmented generation (RAG) for policy procedure grounding and resolution guidance
• Build knowledge ingestion pipelines with refresh/versioning
• Improve answer quality via chunking strategies, embeddings re ranking and context management

Quality, Safety and Evaluation
• Define and run evaluation frameworks: golden datasets, scenario tests, regression tests, and automated scoring.
• Reduce hallucinations and risk by implementing prompt policies, constraints, structured outputs, and verification steps.
• Partner with risk slash compliance to ensure traceability, audit logs, explain ab

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Atika Tech, is seeking the following. Apply via Dice today!

Position: Agentic AI Engineer

Location: Chicago, IL

Duration: 12+ Months

Key Responsibilities

Architecture & Design: Lead the design and implementation of stateful, multi-agent systems using frameworks like LangGraph, CrewAI, or AutoGen.

Agent Orchestration: Develop robust reasoning loops (e.g., ReAct, Chain-of-Thought) and manage complex state, memory, and task hand-offs between specialized agents.

System Integration: Build secure interfaces (e.g., using Model Context Protocol (MCP)) to connect agents with enterprise APIs, databases, and external tools.

Production Excellence: Own the deployment, monitoring, and observability of agents in production using tools like Langfuse or LangSmith to trace reasoning and optimize performance.

Guardrails & Safety: Implement human-in-the-loop (HITL) mechanisms, input/output validation, and ethical guardrails to ensure agents operate safely and within regulatory boundaries.

Leadership: Mentor junior engineers, define coding standards for non-deterministic AI outputs, and drive the technical roadmap for agentic systems.

Required Technical Skills

Programming: Deep proficiency in Python and experience with backend frameworks like FastAPI.

AI Frameworks: Hands-on expertise in LangChain, LlamaIndex, and agent-specific orchestration patterns.

Data Systems: Strong knowledge of Vector Databases (e.g., Pinecone, Chroma), RAG architectures, and knowledge graphs.

Cloud & DevOps: Experience deploying AI workloads on AWS, Azure, or Google Cloud Platform using Docker and Kubernetes.

Evaluation: Proficiency in building automated evaluation harnesses (e.g., LLM-as-a-Judge) to measure accuracy and reduce hallucinations.

Qualifications

Experience: 5 8+ years in software engineering, with at least 2+ years focused on GenAI/Agentic AI implementations.

Education: Bachelor s

Agentic AI Engineer
Enterprise Integrations, Intelligent Automation & AI Platform Delivery

Department: IT & Digital Transformation
Reports to: Sr. Director, Infrastructure & BI
Type: 6 month contract

Location: Remote - US

The Opportunity
Accuris Technologies is executing a company-wide AI transformation across 40+ initiatives spanning Finance, Sales, Marketing, Legal, RevOps, Product, HR, and Customer Experience. We have a funded roadmap, active enterprise AI licenses, and governed integrations already live across our core systems.

We are looking for an Agentic AI Engineer to lead technical delivery-building connectors, agents, and workflows that transform our CRM, ERP, HRIS, and data platforms into a unified, natural-language-driven experience. This role will bring our AI strategy to life through real, production-grade systems.

Core Responsibilities
• Design and build agentic systems that orchestrate across ERP, CRM, data warehouse, HRIS, and BI platforms
• Develop multi-step AI workflows including tool selection, data retrieval, reasoning, and response generation
• Build and extend enterprise integrations, including authentication (OAuth, SSO) and RBAC enforcement
• Deliver AI-powered business solutions such as pricing engines, SDR automation, contract workflows, and executive dashboards
• Implement governance frameworks including audit logging, data lineage, and PII protection
• Partner with business teams to translate workflows into AI-enabled solutions
• Drive adoption through reusable prompts, tools, and training for non-technical users

What We're Looking For
• 3+ years building API integrations with CRM, ERP, or HRIS systems
• Strong Python experience with LLM APIs and SDKs
• Experience with agentic architectures (tool use, function calling, multi-step workflows)
• Familiarity with AI frameworks (LangChain, MCP, or similar)
• Experience with OAuth, SSO/SAML, and enterprise authentication
• Background in data platforms, BI tools, and enterprise data gove

We are a small, mission-driven team leading responsible AI adoption across City government within DT. We work on: Testing and making self-service AI tools available to other departments, Setting technical standards for safe and responsible AI use, and Building and experimenting with prototypes that demonstrate the potential of applied AI. As our Applied AI Engineer, your primary focus will be designing and backend AI cloud infrastructure needed to power AI services. This includes building ingestion pipelines, managing vector databases, integrating LLM APIs, and ensuring backend systems are reliable, observable, scalable, and safe. This role is hands-on, creative, and highly collaborative — ideal for someone who enjoys working at the intersection of technology, product, and impact.Key Responsibilities:Build and manage RAG infrastructure and other cloud tools as needed (e.g., ingestion pipelines, embedding services, retrieval APIs, orchestration).Deploy and maintain vector databases and integrate them with AI services.Develop APIs and backend services that connect prototypes to LLMs and retrieval systems.Implement observability practices including monitoring, logging, alerting, and performance metrics to ensure system reliability and transparency.Use frameworks like LangChain, LlamaIndex, and related libraries to orchestrate retrieval workflows, agents, and hybrid pipelines.Ensure system scalability and resilience, with production-ready practices.Collaborate with the AI Product Engineer to integrate backend services with front-end applications and user pilots.Contribute to standards for safe, responsible AI adoption (data governance, security, and compliance).Experiment with new backend, platform, and cloud tools to stay current with the fast-evolving AI ecosystem.

About the position

Dynasty Financial Partners is building AI-powered systems that directly support advisors, operations teams, and client-facing platforms. We are looking for an AI Engineer to design, build, and operate production-grade AI systems — including LLM-powered agents, RAG pipelines, and evaluation frameworks — that are secure, reliable, and measurable in real business impact.
You will work closely with product managers, data engineers, and software engineers in an agile environment, owning AI solutions end-to-end: from architecture and experimentation through deployment, monitoring, and iteration. This role reports to the Director of Engineering.

Please Note: This job is an IN-OFFICE position located in St. Petersburg, FL. If you are unable or unwilling to fulfill this requirement of the position, please refrain from applying

Responsibilities
• Collaborate & Innovate: Work closely with internal stakeholders, product managers, data engineer, and software engineers to identify opportunities for AI automation. Communicate complex AI system behaviors and limitations to non-technical stakeholders. Stay up-to-date with the latest advancements in LLMs, agent frameworks, and AI orchestration tools, continuously bringing new ideas to improve our multi-agent systems.
• Design & Orchestrate AI Agents: Develop and implement complex multi-agent workflows to solve business problems, using orchestration frameworks to coordinate LLM-powered agents and tools. This includes defining agent roles, interaction logic, and QA processes.
• Design RAG Pipelines and build Knowledge Systems: Work with our Data Engineering team to build and optimize RAG pipelines to give AI agents access to knowledge.
• Integrate & Deploy Solutions: Work with engineers to integrate AI agents into our products and workflows.
• Monitor & Safeguard AI Performance: Establish evaluation frameworks to continuously assess and improve agent performance (accuracy, relevance, response time). Implement auto

Here at Spellbrush , we're passionate about making a good anime game.

We also happen to be the world's leading generative AI studio — we're the team behind niji・journey.

We are currently investigating how AI can be used to help human artists perform masterpieces in the most complex medium of our times: videogames.

Our games are characterized by a no-compromise approach to well-balanced gameplay married to a truthful love of visual arts.

If you love turn-based tactics games, please consider applying!

The Role:

Spellbrush, the world’s leading generative AI studio behind_ niji・journey __ , _ is looking for an LLM Prompt Engineer to bring the characters and world in our mobile turn-based tactics game to life with distinctive flair! If you love games like Fire Emblem and Final Fantasy Tactics and are eager to utilize Generative AI to create evocative gameplay experiences, please apply!

What you’ll do:
• Become the power user and wizarding wordsmith of our LLM models, coaxing out new turns of phrase, emotional responses, and vivid imagery through imaginative prompt engineering.
• Deeply understand our next flagship game’s core narrative, themes, and character motivations and conflicts – then translate these elements into elegant LLM prompts.
• Work with our Creative Director to develop new systems for enabling our game’s characters to freely express themselves in the native game platforms where they interact with players.
• NOTE: You do not need to be currently involved in LLM research or an AI / ML expert to apply - we highly value your writing and creative ability.

You might be a great fit if:
• You endeavor to use LLM’s to revolutionize character communications.

A familiarity with text-based Generative AI and LLM is definitely handy, but moreso than that you understand that LLM’s are working off of datasets and training, and that your finesse in guiding the models will produce outstanding delights of diction.
• You’re eager to push the boundaries of written an

• *Straive**

is a global leader in enterprise-grade Data Analytics and AI solutions, committed to empowering businesses across various industries with cutting-edge technology and expert insights. Backed by EQT, a top private equity firm, we are uniquely positioned to drive innovation through significant investments and an entrepreneurial spirit.

Our core focus is on delivering advanced Data Analytics & AI Solutions. By combining sophisticated technology with subject matter expertise, we deliver material impact on our clients' topline and streamline their operations. We specialize in providing tailored solutions across financial services, CPG, legal, pharma, life sciences, retail and logistics, helping them build robust data analytics and AI capabilities.

With a client base spanning 30 countries, Straive's strategically located teams operate from eight countries and is headquartered in Singapore. This global presence enables us to offer localized expertise with a worldwide perspective.

Join Straive to be part of a dynamic team at the forefront of data analytics and AI innovation. Here, you'll have the opportunity to contribute to transformative projects, supported by significant investments and an entrepreneurial drive fueled by our partnership with EQT.
• *Website: https://www.straive.com/ LinkedIn
• *Job Title: Senior Gen AI Engineer
• *Location: New Jersey- (Hybrid)
• *Type: Fulltime

As a Generative AI Engineer, you will design, develop, and deploy AI-powered solutions using large language models (LLMs), vector databases, and cloud-based infrastructure. You’ll be responsible for building and fine-tuning generative AI models, developing retrieval-augmented generation (RAG) systems, and integrating GenAI capabilities into scalable applications.
• *Key Responsibilities:**

● Develop, fine-tune, and deploy LLM-based applications using frameworks like Senior Gen AI Engineer LangChain, Semantic Kernel, or LlamaIndex.

● Design and implement RAG pipelines using vect

Become a part of our caring community and help us put health first
Become a key driver in shaping the future of AI-powered healthcare. We are looking for a Principal Applied AI Engineer, a technical leader who thrives in ambiguous, high-impact environments and is motivated by solving real problems with pragmatic, elegant, and scalable solutions. This position reports into the AI platform team, ensuring close alignment with platform strategy and delivery. It is for someone who wants autonomy, influence, and the responsibility of setting a high bar for engineering excellence.

Become a key driver in shaping the future of AI-powered healthcare. We are looking for a Principal Applied AI Engineer, a technical leader who thrives in ambiguous, high-impact environments and is motivated by solving real problems with pragmatic, elegant, and scalable solutions. This position reports into the AI platform team, ensuring close alignment with platform strategy and delivery. It is for someone who wants autonomy, influence, and the responsibility of setting a high bar for engineering excellence.

WhatYou'llDo
• Lead the design and build of advanced generative AI systems,spanning LLM-powered applications, multi-agent workflows, RAG, and domain-specific reasoning engines.
• Architect and own robust APIs and platform capabilities that bring AI toreal businessworkflows at enterprise scale.
• Drive the engineering of high-quality data,feature, and evaluation pipelines that support reliable and continuously improving AI behavior.
• Partner with data scientists, platform engineers, and product leaders to transform conceptual ideas into resilient, testable, observable production systems.
• Set engineering standards and elevate team culture, emphasizing clarity, craftsmanship, iteration, and objective measures of excellence.
• Mentor other engineers and guide teams through complex technical decision-making.
• Serve as a thought leader on the practical application of generative AI technologie

About Eleven Recruiting

We are a specialized technology staffing agency supporting professional and financial services companies. Why do we stand out in technology staffing? We listen and act as advisors for our candidates on how they can best add value, find interesting projects, and pave a path for career advancement. We advocate for best pay, diversity in tech, and best job-fit for every candidate we place.

Our client, an investment firm, is seeking a Software Engineer, AI Applications to join their team in New York, NY!

Responsibilities:
• Integrate LLM-powered features — including search, summarization, and workflow automation — into an existing product, working within established codebases and UI patterns.
• Design a data and metadata layer that makes AI outputs explainable, auditable, and reusable across teams.
• Set engineering patterns for how AI capabilities are built, tested, evaluated, and maintained going forward.
• Scope and ship near-term, high-ROI agentic workflows — such as automated meeting prep briefs, pipeline summaries, and relationship intelligence digests.
• Build backend services and APIs that synthesize internal data, activity history, and context into client-ready outputs.
• Take on additional projects and responsibilities as needs evolve across the engagement.

Qualifications:
• 5–8 years of software engineering experience with a strong backend or fullstack foundation.
• 2+ years of focused experience building and shipping LLM-powered applications to production — not just prototypes.
• Solid understanding of how to integrate AI capabilities into existing systems: APIs, data pipelines, and product codebases.
• Hands-on experience with RAG pipelines, prompt engineering at scale, and LLM evaluation.
• Pragmatic product sensibility — able to identify what is worth building, scope it tightly, and ship it.

Preferred:
• Experience with agent orchestration frameworks such as LangGraph or CrewAI.
• Domain exposure in financial services — credit

Joining Collibra’s Artificial Intelligence team

We are looking for an experienced AI Engineer who will design and deliver Artificial Intelligence solutions that improve our customers' experience and enable informed, data-driven decision making. We seek someone excited about working with cutting-edge technologies to build pragmatic, performant AI solutions. You'll collaborate with a team of outstanding builders around the world, characterized by a love for innovative technology, a desire to solve problems, and a continuous pursuit of building simple, elegant products that delight customers and simplify all levels of data engagement. You will work primarily with Data Scientists, other AI Engineers, and Machine Learning Operations Engineers, as well as teams across Collibra.

This is a hybrid role based in our New York office. Our hybrid model means you’ll work from the office at least two days each week. This setup helps us stay connected, work more closely together, and keep making progress as a team.

AI Engineers at Collibra are responsible for
• Monitoring of the larger AI/ML landscape, including emerging techniques and current state-of-the-art approaches
• Transforming prototypes into pragmatic, production-ready solutions which solve impactful business problems
• Creating, operationalizing, and supporting AI/ML models and visualizations to power actionable value and insights
• Evaluating algorithmic results for quality, adaptability, and efficiency
• Contributing to evolving our platforms for Artificial Intelligence and Machine Learning capabilities in support of Collibra’s data products
• Collaborating with cross-functional teams and mentoring junior engineers on AI best practices

You have
• 5+ years of experience delivering production-grade AI/ML projects related to business functions, incorporating advanced techniques (e.g., LLM-based applications, RAG systems, NLP, neural networks, recommendation engines)
• Experience with SQL and relational databases, quer

Job Title: Lead AI Engineer – AI Foundations, LLM Core & Agentic AI

Location- Remote

Role Summary

We are seeking a Lead AI Engineer to drive the design and development of advanced AI systems, with a focus on foundational models, Large Language Models (LLMs), and agentic AI frameworks. This role will lead the architecture and deployment of scalable, production-grade AI solutions that power intelligent automation and next-generation applications.

Key Responsibilities
• Lead the design and development of AI/ML systems with a focus on LLMs and agent-based architectures.
• Build and optimize pipelines for training, fine-tuning, and deploying large language models.
• Architect AI platforms supporting retrieval-augmented generation (RAG), embeddings, and vector databases.
• Develop and manage agentic workflows, orchestration layers, and multi-agent systems.
• Integrate AI capabilities into enterprise applications via APIs and microservices.
• Ensure scalability, performance, and reliability of AI systems in production.
• Collaborate with data scientists, software engineers, and product teams to deliver AI-driven solutions.
• Establish best practices for prompt engineering, model evaluation, and responsible AI.
• Implement monitoring, logging, and continuous improvement for deployed AI systems.
• Stay up to date with advancements in generative AI, LLM frameworks, and tooling.

Required Skills & Qualifications
• Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or related field.
• 7–10+ years of experience in software engineering/AI engineering, with strong hands-on expertise in ML systems.
• Deep understanding of:
• Large Language Models (LLMs) and transformer architectures
• NLP, embeddings, and semantic search
• Retrieval-Augmented Generation (RAG)
• Strong programming skills in Python (preferred) and experience with ML frameworks (PyTorch, TensorFlow).
• Experience with LLM ecosystems and tools (e.g., LangChain, LlamaIndex, vector DBs like Pine

AI Engineer – Agentic AI / LLM Systems

New York | Series A Startup

$180–$250k + Equity

In office (5 days)

No visa sponsorship available

A fast-growing, venture-backed AI company is hiring AI Engineers to build systems where AI doesn’t just respond, but actually learns and executes real enterprise workflows.

The team is developing AI agents that can understand how businesses operate, generate structured instructions, and take action across complex systems, with built-in confidence scoring and human-in-the-loop decisioning.

The role
• Build and deploy agentic AI systems that automate complex, real-world workflows
• Design systems for LLM orchestration, tool usage, and multi-step execution
• Develop production-grade systems in Python
• Implement RAG pipelines, multi-agent systems, and learning workflows
• Build evaluation and confidence frameworks to determine when to automate vs escalate
• Work directly with customers to prototype and ship systems into production

Requirements
• Strong engineering background with Python
• Experience building production LLM systems
• Experience with agentic frameworks, RAG, or orchestration tools (LangChain, LangGraph, etc.)
• Experience building scalable AI systems or automation workflows
• Interest in learning systems, human-in-the-loop workflows, or evaluation frameworks

This is an opportunity to join a small, highly technical team building next-generation AI systems backed by leading investors, working on problems at the edge of what’s currently possible in applied AI.

About Lyzr

Lyzr is a Series A–backed enterprise AI company building a full-stack agent infrastructure platform that helps organizations design, deploy, and govern AI agents. Our platform enables enterprises to move beyond isolated AI use cases and into reliable, production-grade agentic workflows with strong controls around security, accuracy, and compliance.

Recognized by Accenture and Harvard Business School–led innovation ecosystems, Lyzr works with global enterprises to reimagine complex workflows using agentic AI. We focus on making AI agents dependable at scale - so teams can replace fragmented tool stacks with a unified, governed intelligence layer.

About The Job

You won't just be building interfaces; you will be architecting the future of work. You’ll be at the forefront of the "Third Way" of enterprise AI—combining open-source flexibility with enterprise-grade security. You will build Agentic apps on Lyzr, solving complex client requirements by turning fragmented processes into autonomous, intelligent workflows.

What You’ll Do

Build & Orchestrate: Design and deploy sophisticated AI Agents using the Lyzr Agent Studio and SDKs.
Full-Stack Ownership: Develop end-to-end applications with a heavy focus on Python backends and React frontends.
Client Success: Work closely with enterprise clients to translate business requirements into high-performing agentic architectures.
AI Innovation: Implement multi-agent collaboration, memory systems, and RAG-driven orchestrations.

What You Bring

Experience: 4+ years of professional full-stack development.
Tech Stack: Deep proficiency in Python (FastAPI/Django) and React.js.
AI-Native Workflow: You don’t just use a terminal; you leverage Cursor, Claude Code, and other LLM-powered coding tools to ship 10x faster.
LLM Fluency: Familiarity with LLM orchestration, prompt engineering, and the agentic AI landscape.

Location: Based in or willing to work in New York (This is an immediate, onsite/hybrid position).

Why Lyzr?

• *Job Description: AI Agent Engineer**

(Agent Building Team)
• Role:

AI Agent Engineer
• Job Location:

New Jersey
• Word Mode:

Hybrid
• Experience:

4+ years
• *About the Role**

We are looking for an AI Agent Engineer to join client’s Agent Building team to develop intelligent agents and business applications consuming the Enterprise AI Platform, with a focus on agent orchestration, evaluation frameworks, and domain-specific workflows using platform primitives.
• *Key Responsibilities**

· Build agents using AWS Strands SDK, Bedrock AgentCore SDK, and CrewAI orchestration

· Develop agent logic and troubleshooting using strong Python skills

· Implement comprehensive evaluation frameworks for model performance and RAG quality

· Create backend services with Python and integrate with platform APIs

· Build frontend experiences using React JS and Node JS frameworks

· Manage source code with Git/Bitbucket using agile development practices

· Design and debug agent behaviors for production reliability and business outcomes

· Integrate domain-specific RAG pipelines and evaluation metrics

· Consume platform services (gateways, MCP tools, observability) following security patterns
• *Required Skills & Qualifications**

· 4+ years Python development with AI/ML frameworks (CrewAI, LangChain, or equivalent)

· Hands-on experience building production agents with Bedrock AgentCore SDK, Strands SDK/CrewAI

· Strong evaluation framework development (LLM judging, RAG metrics, agent success criteria)

· Full-stack development experience (React JS frontend, Node JS/Python backend)

· Agent debugging and observability skills for complex multi-agent workflows

· Experience consuming enterprise API platforms (REST/GraphQL/OAuth2) securely
• *Nice to Have**

· Domain expertise in financial services use cases for agentic AI

· Multimodal agent development (text + image/audio processing)

· Previous CrewAI production deployments with custom tools and memory management
• Integers.

Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration)

Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:
• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
• Design, develop, test, deploy, and support AI soft

Senior Lead AI Engineer (AI Foundations, LLM Customization and Finetuning)

Overview:

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:
• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
• Design, develop, test, deploy, and support AI software com

The Intelligence Platform team builds scalable, production-grade systems that power high-quality, user-centric intelligence across Apple’s operating systems. We focus on designing and operating large-scale ML systems leveraging Generative AI, Large Language Models, RAG architectures, and emerging agentic AI patterns. Our goal is to deliver reliable, low-latency, and privacy-preserving AI capabilities at scale.

Description

We are looking for a Software Engineer with strong systems and engineering expertise to build and scale LLM-powered systems in production. This role focuses on designing robust infrastructure for LLM serving, tool-use orchestration, and agentic workflows.

You will work at the intersection of ML and systems engineering-translating advanced AI capabilities into efficient, scalable, and reliable systems. You will play a key role in shaping system architecture, optimizing performance, and ensuring production readiness of LLM-driven features across Apple platforms.

","responsibilities":"* Design and build scalable systems for LLM inference, orchestration, and agentic workflows (e.g., tool-use pipelines, multi-step reasoning systems).
• Productionize LLM-based solutions with a focus on latency, throughput, reliability, and scalability.
• Architect and maintain infrastructure for model serving, batching, caching, and context management.
• Develop and optimize pipelines for RAG systems, retrieval infrastructure, and data flow across components.
• Partner with modeling teams to integrate models into production systems, ensuring alignment with performance and product requirements.
• Build monitoring, evaluation, and feedback systems to ensure high-quality and robust model behavior in production.
• Drive system-level optimizations across the stack, including distributed systems, concurrency, and resource management.

Preferred Qualifications

Experience with LLM serving systems, inference optimization, batching strategies, or caching (KV/prefix).

Experie

About Tessera Labs Tessera Labs is redefining how enterprises adopt and operationalize Artificial Intelligence. Backed by Foundation Capital and led by a world-class founding team, we build multi-agent AI systems that can automate complex business workflows across platforms like SAP, Salesforce, Workday, Snowflake, MuleSoft, and more. Our mission: Bring real AI automation to the enterprise — with speed, precision, and measurable impact. We move fast, operate with extreme ownership, and build at the frontier of applied AI.

Job Summary

As we build to the next level, we’re looking for a top-quality AI engineer with a strong focus on AI agents - someone who knows how to leverage LLMs, both open-source and closed, in combination with complex tool-calling hierarchies and operational patterns.

This is an opportunity to build scalable, secure, and high-impact AI technologies for the future of enterprise. If you thrive in high-growth, fast-moving environments and are passionate about AI, ML, and AI agents, we want to hear from you.

Key Responsibilities

1. AI Agent Building (60%)
• Develop complex multi-step agentic pipelines around open- and closed-source LLMs.
• Build tools enabling AIs to interact with critical enterprise software platforms.
• Ensure AI designs align with business objectives and industry best practices.​

2. ML development and fine-tuning (30%)
• Create data generation and processing pipelines to train and fine-tune custom ML models.
• Implement and manage training and evaluation pipelines for LLMs.

3. Deployment and AI Systems Infrastructure (10%)
• Manage AI infrastructure across platforms such as AWS, Azure, or GCP.​
• Deploy inference endpoints and serve AI and LLM technologies as part of our core product infrastructure.

Required Qualifications
• Earned a Bachelor’s degree, Master's degree or Ph.D. in Computer Science, Engineering, or a related field.​
• 5+ years of experience in software engineering, platform engineering, or related roles.​
• P

We are looking for a driven AI Engineer to join our engineering team. In this role, you will focus on building, testing, and deploying autonomous AI agents and multi-agent systems. You will bridge the gap between traditional software engineering and modern Generative AI, working to enable LLMs (Large Language Models) to interact with external tools, APIs, and data sources.
• Equifax has a hybrid work schedule that allows for 2 days of remote work (Monday and Friday), with 3 days onsite (Tuesday, Wednesday, Thursday) every week.
• This role reports to our office in Alpharetta, Georgia
• This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support.
• This is a direct-hire role and is not open to C2C or vendors.

What you’ll do
• Design, develop, and operate high scale AI applications across the full engineering stack.
• Design, develop, test, deploy, maintain, and improve software that has AI / LLM integrations in it.
• Apply modern software development practices (serverless computing, microservices architecture, CI/CD, infrastructure-as-code, etc.)
• Work across teams to integrate our systems with existing internal systems, Data Fabric, CSA Toolset.
• Participate in technology roadmap and architecture discussions to turn business requirements and vision into reality. Participate in a tight-knit, globally distributed engineering team.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on network, or service operations and quality.
• Research, create, and develop software applications to extend and improve on Equifax Solutions. Manage sole project priorities, deadlines, and deliverables.
• Collaborate on scalability issues involving access to data and information. Actively participate in Sprint planning, Sprint Retrospectives, and other team activity

What experience you need
• Bachelor's degree or equivalent experience
• 5+ years of software engineering experi

At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.

Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers’ expectations while making a real impact for our company through our shared purpose.

When you join our company, we want you to feel valued, supported and proud to work here. That’s why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers.

Sr. Staff Machine Learning Engineer – AI Agent Platform

Position Description

GEICO is seeking an exceptional Sr. Staff ML Engineer to join our AI organization. You will serve as a technical leader and key architect for GEICO's virtual assistant platform that elevates productivity for 30K+ internal associates and the customer experience for millions of policyholders.

Sr. Staff AI Agent Platform Engineers set the technical vision and drive the architecture of multi-tenant services that power the building, testing, deployment, and hosting of LLM-based AI agents. This includes multi-agent orchestration, standardized interoperability protocols (MCP, A2A), AI agent skill ecosystems with marketplace and governance capabilities, production-grade harness & context engineering, and guardrail frameworks for safe autonomous operation at enterprise scale.

Responsibilities
• Technical Vision & Architecture: Define the long-term technical strategy for GEICO's AI agent platform — including multi-agent orchestration, AI agent lifecycle management, evaluation frameworks, skill registries and marketplace, and workflow orchestration.
• AI Agent Skills & Marketplace: Architect an enterprise skill ecosystem — reusable capability packages that encode domain expertise and workflows into portable, discoverable modules. Build and govern an internal skill marketplace with versioning, security vetting, approval workflows, progressive

Jobright is your personal AI job search agent that transforms the job search process into a fast, expert-guided journey. They are seeking an AI Engineer to build and scale business-facing AI agents, managing the entire lifecycle from prototype to production.

Why Join Us
• Build real, production AI agents used by real users
• High ownership and impact
• Work at the intersection of AI, agents, and product
• Shape how people experience AI-driven job search

Responsibilities
• Design, build, and deploy end-to-end AI agents for business and user-facing applications
• Develop agent-driven applications, including user interaction flows and APIs
• Build and maintain agent infrastructure, including orchestration, monitoring, and reliability
• Implement and iterate on agent evaluation (quality, reliability, latency, cost)
• Collaborate closely with product and business teams to translate real problems into agent solutions
• Continuously improve agent performance using real-world feedback and data

Qualification

Required
• Familiarity with at least one programming language (e.g. Python, JavaScript, TypeScript)
• Experience with writing a lot of code, backend or full-stack
• Experience building applications
• Strong interest in AI agents and applied LLM systems
• Ability to own features end-to-end, from design to production

Preferred
• Hands-on experience using and deploying AI agents, such as: Claude Code, Codex, ClawdBot, OpenCode, or similar agent frameworks/tools
• Experience with agent orchestration, tooling, or infra
• Experience building production AI products rather than demos
• Experience in fast-moving startup environments
• Product-minded approach and comfort with ambiguous problems