Jobs

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

BPX GenAI Squad Data Scientist requirement

Data Scientist AIML P2P3

Experience 6- 8 Years

Skillset Required

Expert level understanding of Machine LearningDeep Learning concepts techniques algorithms

Hands on working experience on building end to end MLDL solutions

Expert level proficiency in Python programming is a prerequisite

Strong understanding of objectoriented programming and design principles

Experienced with common data science packages in Python like Pandas Numpy Matplotlib and frameworks such as Tensorflow Pytorch

Handson experience in RESTful APIs development with FlaskAPI FastAPI

Excellent understanding of NLP concepts libraries including Word2Vec TFIDF NLTK SpaCy Gensim BERT GloVe etc

Must have experience in development of NLPNLGNLU projects

Deep understanding of Transformer Architectures including BERT GPT DistillBert

Good understanding of Generative AI concepts like Large Language Models Finetuning Evaluating LLMs PEFT RAG Embeddings Vector Databases etc

Experience in frameworks such LangChain LlamaIndex

Experience with Large Language models such as Llama GPT PaLM etc

Experience with Amazon Bedrock Azure OpenAI GCP GenAI Studio

Expertise in training and finetuning LLMs would be preferred

Proficientcy in model development deployment and optimization techniques

Certifications in GenAIAIML preferred

Experienced in deploying AI solutions in cloud environments

Working knowledge in any of the major cloud services AWSAzure

Working knowledge in either of AWS SageMakerAzure Cognitive ServicesGoogle Vertex AI

Certification in any of the Cloud Platforms AWSAzureGCP

Good problemsolving and critical thinking skills

Familiarity with version control systems Git

Knowledge of SQL NoSQL

Key Roles Responsibilities

Create and maintain highquality reusable code components and libraries for future use

Perform rigorous testing and validation to ensure models perform accurately and efficiently in various conditions

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

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

About the position

Senior AI Engineer – Real Estate Tech We’re building an innovative product in the real estate space and seeking a Senior AI Engineer to join our founding AI team. This role involves turning generative AI concepts into production-ready features and shaping intelligent software experiences.

Responsibilities

AI Agent Development: Build autonomous and conversational AI agents to enhance productivity and automate workflows.AI/ML System Development: Architect scalable AI systems using AWS AI services and open-source frameworks.Full-Stack Integration: Collaborate with Ruby on Rails backend and React frontend teams for AI feature integration.Data Pipeline Management: Design robust pipelines for real estate datasets to support model training and inference.Performance & Monitoring: Optimize deployed models, APIs, and agents for reliability, accuracy, and cost efficiency.Innovation & Research: Apply LLMs, RAG, and agentic AI to solve complex problems.Technical Leadership: Mentor peers, contribute to coding standards, and influence AI strategy.Lifecycle Ownership: Handle AI development from concept to deployment and iteration.Requirements

5+ years in AI, ML, or software engineering with production AI experienceProficient in Python ; experience with PyTorch, TensorFlow, LangChainHands-on cloud deployment ( AWS preferred )Strong understanding of LLMs, Generative AI, RAG, data structures, algorithms, distributed systemsExcellent collaboration and cross-functional teamworkNice-to-haves

Experience with Ruby on Rails and React integrationKnowledge of vector databases (Pinecone, FAISS, Weaviate)Familiarity with MLOps tools (SageMaker, MLflow)Interest in real estate technology

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)

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

Principal Applied AI Engineer, Finance

We are seeking a Principal Applied AI Engineer to lead the design and delivery of next-generation AI and predictive models that transform financial decision-making at scale. This role sits at the intersection of advanced machine learning, agentic AI, and software engineering, with a strong focus on production-grade AI systems, intelligent automation, and predictive modeling.

The ideal candidate is both a strategic technical leader and hands-on builder-capable of architecting complex AI systems with a software engineering mindset, influencing organizational direction, and delivering measurable business impact. You will drive innovation in Generative AI, lead the evolution toward agentic AI systems, and establish best practices across modeling, deployment, and governance in a finance context.

Key Responsibilities
Agentic AI & Generative Systems
Architect and lead the development of agentic AI systems that automate and augment finance workflows (e.g., forecasting, reporting, and decision support).Design and implement multi-agent systems leveraging LLMs, tool-use frameworks, and orchestration patterns (e.g., RAG, model chaining, dynamic prompting).Translate cutting-edge research in LLMs and agentic AI into scalable, production-ready solutions.Establish guardrails, evaluation frameworks, and responsible AI practices to ensure safe, compliant, and reliable outputs.Design fault-tolerant, observable agent systems with clear failure modes and recovery strategies

Predictive Modeling & Customer Behavior Forecasting
Lead the design and implementation of advanced predictive models, including time series forecasting and attrition prediction across customer segments.Develop interpretable, production-grade models that drive retention strategies and financial planning.Define and standardize evaluation metrics, validation frameworks, and monitoring systems for model performance and drift detection.Translate complex predictive insights into a

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.

Strategic/Functional

Define and drive the organization's AI strategy and roadmap aligned with business goals
Educate leadership and cross-functional teams on AI capabilities, use cases, and best practices
Identify high-impact AI/ML use cases across departments
Provide guidance on responsible AI, governance, and compliance, especially in Public Sector settings
Collaborate with stakeholders to translate business needs into AI-driven solutions
Technical

Design high-level AI/ML architectures and solution frameworks
Evaluate and recommend tools, platforms, and frameworks (e.g., cloud AI services)
Guide teams on data readiness, model lifecycle, and deployment strategies
Ensure scalability, security, and performance of AI solutions
Stay updated with the latest trends in Generative AI, LLMs, and AI platforms


Required Skills & Experience:

8+ years of experience in AI/ML, Data Science, or Solution Architecture
Proven experience as an AI Architect / AI Consultant / ML Architect
Strong understanding of AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.)
Experience with cloud platforms (AWS, Azure, or GCP AI services)
Ability to communicate complex AI concepts to non-technical stakeholders
Experience in defining AI strategy and roadmaps


Preferred Qualifications:

Experience working with Public Sector / Government clients
Exposure to Generative AI / LLMs (e.g., GPT, RAG architectures)
Knowledge of AI governance, ethics, and compliance frameworks
Prior experience in advisory or consulting roles

We are hiring senior engineers who build fast, think AI-first, and can take agentic AI from prototype to production. You will design, ship, and operate agentic systems that combine large language models (LLMs), tools/functions, planning, memory, evaluation, and multi-agent communication. You will work primarily in Python for AI services and integrate with our enterprise stack (TypeScript/Angular, .NET/C#, SQL Server, Azure), delivering trustworthy, cost-efficient, low-latency experiences in real customer workflows.

What You'll Do!
Build agentic AI applications on Azure AI Foundry: Azure OpenAI models, Prompt Flow, tools/function-calling, evaluations, vector search (Azure AI/Cognitive Search), and orchestration for multi-step reasoning and tool use.Design memory & grounding: implement episodic/semantic/long-term memory with vector/graph stores; architect RAG pipelines and retrieval strategies that improve factuality and reduce latency/cost.Integrate via Model Context Protocol (MCP) to standardize tool/skill access; design agent-to-agent communication, delegation, and event-driven workflows.Connect agents to Microsoft Fabric (OneLake, Lakehouse, Warehouse, Real-Time Analytics) and Dataverse entities/workflows; ensure lineage, governance, and auditability.Develop AI-native backend services in Python (FastAPI, asyncio) with evaluation harnesses, observability, and cost/latency/quality dashboards.Embed AI features into the MTech stack: TypeScript/Angular UIs, .NET/C# services, SQL Server, NServiceBus, Azure DevOps pipelines, and Ionic/Cypress where applicable.Use AI-augmented development tools like GitHub Copilot, Bolt, Cursor, Replit, and vibe-coding workflows to accelerate delivery, test generation, refactoring, and documentation.Implement safety & reliability: guardrails, red-teaming, PII protection, prompt hardening, regression tests, automated evaluations; uphold SLO/SLA excellence in production.Implement full cycle agentic engineering: design → model/tool selecti

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

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

Job Title: AI Agent Engineer

Location: Reston, VA ( Onsite)

Job Description:

Required Skills:

Strong experience in AI/ML concepts and model development

Hands-on experience with Large Language Models (LLMs)

Experience with OpenAI API or similar AI platforms

Good understanding of RAG architecture and implementation

Experience with embeddings and vector databases (e.g., Pinecone, FAISS, Weaviate)

Proficiency in Python or Go (Golang)

Experience with AWS services (EC2, S3, Lambda, SageMaker, etc.)

Knowledge of REST APIs and microservices architecture

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

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

WHO WE ARE

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry's largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

Role Snapshot

We're hiring a hands-on Agentic AI engineer to build bidder-adjacent agents that improve campaign performance using RAG + tool-using workflows in a closed-loop ACE (Observe Reason Act Evaluate). This is not a classic "train a model and deploy it" role—this is agentic decisioning + evaluation + safety in a low-latency AdTech environment.

What You'll Do
• Build bidder-adjacent agentic workflows that recommend/execute campaign control actions (targeting constraints, budget & pacing levers, bid modifiers, supply/inventory selection, creative routing).
• Implement production-grade RAG: retrieval from policies/playbooks, campaign history, aggregates, and near-real-time telemetry; optimize grounding and reduce hallucinations.
• Create safe tool/action interfaces: idempotent execution, audit logs, dry-run + approval gates, rate limits, rollback/fallback behaviors.
• Own AgentOps: eval harnesses, regression suites, online experimentation (A/B), metrics tied to outcomes (CPA/ROAS, pacing, quality, margin).
• Add observability end-to-end (tracing prompts/retrieval/tool calls/latency) and reliability

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

We are hiring as many as two Senior AI Engineers who can architect and ship agentic systems, swiftly. You will be embedded in the full product lifecycle: ideation, prototyping, testing, and iteration across multiple concurrent concepts. Our first platform targets compliance automation in regulated industries, starting with affordable housing, designed to scale horizontally. When something proves out, you go deep. When it doesn't, you let it go without sentiment and move to the next. If the products you launch draw early signs of product-market fit, the resources will be assigned accordingly to seize upon the opportunity and iterate.

What You'll Do

Design and deploy multi-agent orchestration systems using frameworks like LangGraph, CrewAI, AutoGen, or equivalent, and know when to roll your own
Build full-stack prototypes fast enough to validate or kill an idea within weeks, not quarters
Own the technical architecture on 2-4 parallel concepts at any point in time
Integrate LLMs, RAG pipelines, structured data sources, and external APIs into coherent product experiences
Oversee commercialization and enterprise-upgrading to bring MVPs to full launch
Instrument everything so decisions are data-driven, not vibes-driven
Collaborate directly with the principals. There is no middle layer here

Who You Are

You have built real agentic systems, not just demo apps. You understand tool use, memory architectures, multi-agent orchestration, and evaluation at a production level. You know the difference between a clever prototype and something that actually holds up under load
You move fast and you ship. You have launched products at startups where speed was the strategy, not just a nice-to-have. Weeks, not quarters
You are full-stack by necessity, not by title. Frontend, backend, infra, pipelines. You do what needs doing and figure out the rest on the fly
You have strong opinions about what makes software work and zero patience for unnecessary complexity. You woul

This role is part of the Jobright Direct Hiring Network, where top companies like Cresta AI, Plaud, Mercor, OpenArt, and 1,500+ others hire top talent directly through our platform.

This is not a mass job posting. Only select, high-signal candidates are invited and recommended directly to hiring teams

Hiring Company: Creao AI

One-liner: CREAO is redefining the relationship between people and software by empowering users to create custom, conversational AI applications using natural language.

Salary:

Why Join Us:

Role Responsibilities

• Design, develop, and deploy AI agents using LLMs (e.g., GPT, Claude, open-source models)

• Build multi-step reasoning, planning, and tool-using agent workflows

• Integrate AI agents with internal systems, APIs, databases, and third-party services

• Implement evaluation frameworks to measure agent performance, reliability, and safety

• Optimize prompts, memory systems, retrieval pipelines, and agent architectures

• Collaborate with product, engineering, and design teams to translate real-world problems into AI-driven solutions

• Improve system scalability, latency, and cost efficiency

• Monitor agent behavior in production and continuously iterate based on feedback and data

• Ensure responsible AI practices, including privacy, safety, and bias mitigation

Qualitications

Required

• Strong software engineering skills in Python, TypeScript, or similar

• Experience working with LLMs, AI frameworks, or ML systems

• Understanding of agent architectures, such as: Tool use / function calling, Planning & reasoning, Memory & retrieval (RAG)

• Experience integrating APIs, databases, and distributed systems

• Ability to ship production-ready systems with reliability and observability in mind

Preferred

• Experience with frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, or similar

• Experience with vector databases (Pinecone, FAISS, Milvus, etc.)

• Knowledge of evaluation methods for generative AI systems

• Experie

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

Who are we?

Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.

We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.

Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.

Join us on our mission and shape the future!

Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and Agents. We believe that our work is instrumental to the widespread adoption of AI.

We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.

Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.

Join us on our mission and shape the future!

Why this role?We’re a fast-growing startup building production-grade AI agents for enterprise customers at scale. We’re looking for Software Engineers with Applied AI experience who can own the design, build, and deployment of agentic work

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

Databricks is a data and AI company that helps organizations build and productionize AI applications. The AI Forward Deployed Engineering team is seeking an AI Engineer to develop cutting-edge GenAI solutions and serve as a trusted technical advisor to federal government customers.

Responsibilities
• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI Research to solve customer problems
• Own production rollouts of consumer and internally facing GenAI applications
• Serve as a trusted technical advisor to customers across a variety of domains
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap

Skills
• U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information
• Experience working with U.S. federal civilian, state, or local agencies
• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.)
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving business value through AI
• Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed

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

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

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

Job Family: Software

Req ID: 497124

We are seeking a Senior Agentic Software Engineer to design, build, and operate production-grade AI agent systems that augment and automate real business workflows.

This role goes beyond prompt engineering or demo-level prototypes. You will own agentic systems end-to-end—from architecture and integration with existing services, to reliability, evaluation, and long-term operation. You’ll work closely with product, platform, and domain experts to deliver agentic capabilities that are trustworthy, scalable, and measurable, while helping define how agentic systems are built across the organization.

What You’ll Do:
• Design, build, and operate agentic systems that reliably complete real tasks, not just answer questions.
• Architect agents that support planning, memory, tool use, and multi-step execution, selecting appropriate patterns (single-agent, multi-agent, workflow-driven, human-in-the-loop) based on problem constraints and risk.
• Balance autonomy with control by designing agents that are predictable, debuggable, secure, and aligned with business goals.
• Build agents using modern frameworks (e.g., LangGraph, LangChain, Semantic Kernel, AutoGen, or equivalent), implementing structured outputs, tool-calling, reflection, and state management.
• Design and implement MCP- and/or RAG-based integrations as first-class mechanisms for how agents access tools, data, and context.
• Enforce security, consent, access control, and observability across all agent–tool interactions, partnering with platform teams to establish and evolve MCP integration standards.
• Integrate agentic systems into existing services and platforms via APIs and backend services, owning production readiness end-to-end.
• Define what “good” looks like for agents using clear metrics (e.g., accuracy, success rate, latency, cost, failure modes), and use those metrics to drive continuous improvement.
• Build automated evaluation pipelines (offline tests, synthetic dat

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

Security Clearance is required for this role

Job Title: AI/ML Engineer

Job Type: Full-Time

About Us:

micro1 is the end-to-end human data infrastructure behind AGI. Our AI recruiter model is used by frontier AI labs and Fortune 10s to source, vet, and deploy PhDs and professors from the world’s top universities at scale. These experts are placed directly into the training loops of the most advanced AI systems, powering the breakthroughs that move models forward. Our data platform converts their expertise into high-signal training datasets, and our talent management tooling measures, routes, and improves performance at scale.

Job Summary:

Join our team as a AI/ML Engineer and play a pivotal role in driving mission-critical government initiatives while also contributing to micro1’s proprietary AI infrastructure, you’ll harness advanced large language models (LLMs), retrieval-augmented generation (RAG), and multi-agent orchestration to deliver secure, scalable, and impactful machine learning systems. You’ll work closely with cross-functional experts, leveraging frontier AI platforms and the latest in agentic AI tooling.

Key Responsibilities:
• Design, implement, and optimize AI/ML models particularly leveraging LLMs, RAG, and prompt engineering for production grade applications.
• Develop and orchestrate multi-agent systems using frameworks such as LangGraph and LangChain.
• Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
• Build robust data pipelines, manage ETL processes, and develop metadata catalogs and ontologies to ensure high-quality data for AI training and inference.
• Create and maintain REST APIs and SDK integrations to facilitate seamless data and model interactions.
• Collaborate with product, security, and engineering teams to ensure best-in-class delivery, following secure coding and DevOps best practices (CI/CD).
• Document technical decisions and communi

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

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

Our client is a world-renowned biotech powerhouse, but they're currently operating with the speed and ambition of a startup in the AI space. We aren't just looking for someone to build chatbots; we need a Senior Agentic AI Modeler who can architect systems that actually reason, plan, and solve complex problems autonomously.

If you’re obsessed with the 'bilingual' intersection of traditional predictive modeling and the new frontier of Multi-Agent orchestration (and you've already started playing with MCPs), we should talk.
• You'll have the freedom of a heavily remote schedule, with the added benefit of joining the team in the office roughly once a week (about 5 days a month) to stay connected.

About the Role:

Agentic System Design & Development
• Architect and implement autonomous and semi-autonomous agent workflows using modern frameworks (LangChain, OpenAI Assistants, Semantic Kernel, LlamaIndex, CrewAI, DSPy, etc.)
• Build agents capable of multi-step reasoning, task decomposition, planning, and tool execution.
• Develop tooling ecosystems—function APIs, retrieval endpoints, evaluators, monitoring hooks—for agent orchestration.
• Prototype, fine-tune, and optimize LLMs, RAG systems, and multi-agent architectures for reliability and low hallucination rates.

Modeling & Prompt Engineering
• Create robust prompt pipelines, templates, and routing strategies for diverse commercial/analytics use cases.
• Optimize agent behaviors via prompt distillation, chain-of-thought design, system message tuning, guardrails, and evaluation frameworks.
• Use datasets and logs to refine agent behavior through supervised fine-tuning or RLAIF where applicable.

Solution Integration & Delivery
• Integrate agents with enterprise systems, APIs, data stores, CRMs, search tooling, and business applications.
• Implement observability for agent decision-making: trace logs, tool call audits, success/failure rates, safety events, drift.
• Partner with engineering and MLOps to deploy agentic

DeVry University strives to close our society’s opportunity gap and address emerging talent needs by preparing learners to thrive in careers shaped by continuous technological change. Through innovative programs, relevant partnerships, and exceptional care, we empower students to meaningfully improve their lives, communities, and workplaces.

Our colleague experience is an area of obsessive focus. At DeVry University, we care about you. Because, only through you can we deliver our unique Care Formula to our learners and partners.

Overview

The Applied AI Prompt Engineer designs, optimizes, and maintains the prompts, agent behaviors, context structures, and Retrieval-Augmented Generation (RAG) workflows that power DeVry’s enterprise AI ecosystem—including Copilot, ChatGPT, agentic workflows, and internal knowledge tools.

This is a hybrid role blending prompt engineering, operational AI lifecycle management, and cross-functional collaboration. You will rapidly prototype prompt variations, run evaluations, maintain knowledge pipelines, and ensure outputs remain accurate, compliant, and aligned with DeVry’s tone and policies.

The ideal candidate is fast, curious, experimental, and skilled at translating human-to-human support scenarios into reliable AI-driven interactions.

Key Responsibilities

Prompt Design & Optimization
• Design and maintain high-quality prompts, and agent instructions for enterprise AI platforms.
• Rapidly prototype and iterate prompt variants using structured experimentation, evaluation metrics, and A/B testing.
• Build evaluation rubrics, structured test cases, and prompt datasets to measure accuracy, tone, consistency, and policy alignment.
• Adapt prompts for higher-education use cases (e.g., advising, HR, faculty support, IT, student services) while maintaining institutional tone and compliance.

RAG & Knowledge Integration
• Curate and manage document ingestion, embeddings, and knowledge base updates to ensure relevant, current, and contex

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

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.

Job Title: AI/ML Engineer

Job Type: Full-Time

Job Summary

Join our team as a AI/ML Engineer and play a pivotal role in driving mission-critical government initiatives while also contributing to proprietary AI infrastructure, you’ll harness advanced large language models (LLMs), retrieval-augmented generation (RAG), and multi-agent orchestration to deliver secure, scalable, and impactful machine learning systems. You’ll work closely with cross-functional experts, leveraging frontier AI platforms and the latest in agentic AI tooling.

Key Responsibilities
• Design, implement, and optimize AI/ML models particularly leveraging LLMs, RAG, and prompt engineering for production grade applications.
• Develop and orchestrate multi-agent systems using frameworks such as LangGraph and LangChain.
• Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
• Build robust data pipelines, manage ETL processes, and develop metadata catalogs and ontologies to ensure high-quality data for AI training and inference.
• Create and maintain REST APIs and SDK integrations to facilitate seamless data and model interactions.
• Collaborate with product, security, and engineering teams to ensure best-in-class delivery, following secure coding and DevOps best practices (CI/CD).
• Document technical decisions and communicate complex concepts clearly to both technical and non-technical stakeholders.

Required Skills And Qualifications
• Proficiency in Python for AI/ML development, including experience with REST APIs and SDK integration.
• Hands-on experience with LLMs, RAG systems, and prompt engineering in production environments.
• Familiarity with multi-agent orchestration, tool use, and frameworks like LangGraph and LangChain.
• Deep understanding of cloud AI services (AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, AWS Bedrock).
• Background in building and maintaining data pipelines, ontologies, me

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

• *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.

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