About Amigo

Amigo partners with healthcare organizations to deploy robust AI infrastructure that directly serves patients and providers. Our agents handle clinical workflows and patient engagement across the entire journey: pre-visit intake, care navigation, post-visit care plans, patient monitoring, and more.

We're fresh off our Series A backed by Tier 1 investors like Madrona, General Catalyst, and Optum Ventures. Our work is validated with leading academic medical institutions. Our agents have reached 3M+ patient encounters and are on track to 10x this year.

About this role

The Applied AI Engineer role at Amigo is a launchpad. You'll ship production AI agents end-to-end — writing the code, shaping product decisions, and sitting with customers as they deploy — and in doing so, you'll build the exact skill set that opens doors to the next chapter of your career at Amigo.

This role is designed to help you grow into other parts of the company. Applied AI Engineers move into one of four paths within 6–12 months:

• Applied AI: stay in the org; go deeper on agent architecture, verification frameworks, and the hardest customer problems; become a technical leader on the applied team

• Product Management: if you gravitate toward roadmap, discovery, and shaping what we build next

• Sales Engineering: if you thrive in pre-sales, technical storytelling, and closing enterprise deals

• Software Engineering: if you want to go deeper on platform, infrastructure, and core systems

You won't have to guess which fits. This role will actively help you explore each path, give you projects that stretch in those directions, and sponsor the internal transition when you're ready. People who want to stay on the applied side long-term can do that too — but this role is explicitly built so you don't have to.

What you'll do

• Implement context graphs that enable agents to select the right reasoning mode (lookup, pattern recognition, exploration) based on problem complexity

• Build and optimize agent configurations, including static personas, dynamic behaviors, and functional memory systems

• Design bounded Operational Patient Domains (OPDs) with explicit inclusions, exclusions, capabilities, and escalation rules

• Implement verification loops and simulation-based testing to validate agent performance against customer KPIs

• Write Python code for tool integrations and API orchestration within customer environments

• Build evaluation suites that gate deployments using customer-specific success metrics

• Collaborate with domain experts through structured interviews to capture reasoning patterns and clinical protocols

• Support technical power users through git-based workflows for rapid iteration

• Implement adversarial testing to systematically identify and prevent failure modes

• Ensure agents maintain audit-ready provenance with version pinning and evidence links

• Contribute to systematizing implementation patterns across different problem domains

What we're looking for

• 2+ years of production software engineering experience

• Strong Python skills including proper use of typing, and experience building highly reliable systems that interact with external APIs (schema design, retry strategies, error propagation)

• Experience with LLMs, prompt engineering, and building on AI platforms

• Ability to implement systems with strict reliability requirements

• Understanding of testing and verification methodologies

• Experience working directly with customers or stakeholders to deliver technical solutions

• Familiarity with git workflows and collaborative development

• Strong debugging and problem-solving skills for complex systems

• Ability to balance theoretical concepts with practical implementation constraints

• Clear technical communication for both engineering and non-technical audiences

Nice to have

• Experience in regulated industries (healthcare, finance, legal)

• Background with simulation, synthetic data, or evaluation frameworks

• Understanding of distributed systems and service-oriented architectures

• Experience with observability and monitoring in production environments

• Familiarity with compliance requirements (HIPAA, SOC 2, GDPR)

Benefits

Health & Wellness

• Comprehensive health, dental, and vision insurance

• Daily catered lunch and dinner

• Mental health support and wellness coaching

• Flexible wellness stipend for fitness, therapy, or personal growth

Growth & Development

• Annual learning budget for courses, books, or conferences

• Conference attendance budget for professional development

• Annual team offsite

• Academic collaboration opportunities

• Unlimited PTO

Our Core Values

1. Patients Win, We Win

   If patients aren't getting better care, we haven't earned the right to scale. Every internal decision gets pressure-tested: does this make patients' lives better? If we can't draw the line, we question why we're doing it.

2. High Standards, High Care

   We hold a high bar for the team because patients are counting on us to get this right. But high standards only work with genuine investment in each other. You can take risks, admit mistakes, and challenge ideas—not despite our standards, but because of them.

3. Thoughtful Urgency

   We move fast by default, but speed without judgment is recklessness. The discipline is knowing which decisions are reversible vs. not. In healthcare AI, the companies that win will be fast everywhere they can be and careful everywhere they must be. We build the muscle to do both.

4. Intensely Measured

   We instrument patient outcomes, provider ROI, system performance, and clinical accuracy. But data without action is surveillance. Every metric should have an owner, a threshold, and a response plan. If we're measuring something but never acting on it, we stop measuring it.

Who Builds With Us

• Low ego: Politics and territory don't interest you. The best ideas win, regardless of who has them.

• Direct: You say the hard thing, challenge ideas openly, and commit fully once decided.

• High agency: You thrive on trust rather than instruction. When you see something is broken, you fix it. You don’t file tickets and wait for someone else.

• Bar of excellence: You hold yourself to a bar most people wouldn't, and you want teammates who do the same.

• Skeptical: You push back on rules that don’t make sense and question assumptions that haven’t earned their place.

Please mention the word **READABLE** and tag RMjYwNTo0YzQwOjQwOjc1Nzk6MDplZDIyOmQzMzc6MQ== when applying to show you read the job post completely (#RMjYwNTo0YzQwOjQwOjc1Nzk6MDplZDIyOmQzMzc6MQ==). This is a beta feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.

About Us:

We are embarking on an exciting era of Data & AI that will transform work and society. Our organization is at the forefront of this innovation, dedicated to assisting clients in optimizing and reinventing their businesses through a substantial investment in Data & AI.

With a team of over 77,000 professionals, we are equipped to tackle industry challenges backed by exceptional talent, experienced innovation, strategic investments, and a powerful ecosystem.

Your Role:

As a Forward Deployed AI Engineer, you will be instrumental in designing, building, and deploying cutting-edge AI systems powered by Large Language Models (LLMs). Your contributions will span the entire AI lifecycle, from research and fine-tuning of foundation models to prompt engineering, systems integration, and deployment in production environments. You will be responsible for enhancing the performance and alignment of our AI systems.

Key Responsibilities:

Design, develop, and optimize AI prompts and applications using foundation models like LLMs. Architect and implement generative agent systems to manage complex tasks effectively. Develop application strategies focusing on both user experience and backend systems. Evaluate and optimize AI system architectures, applying best practices and relevant frameworks. Conduct thorough code reviews, offering expert guidance for enhancements and issue resolution. Build and maintain scalable machine learning infrastructure and training pipelines. Apply advanced evaluation techniques to ensure model robustness, safety, and fairness. Collaborate closely with cross-functional teams to align AI systems with business objectives. Support troubleshooting during testing and production phases. Document technical methodologies and innovations for effective knowledge sharing. Please note that travel may be required for this role, ranging from 0% to 100% based on business needs.

Qualifications:

Minimum 3 years of experience in designing and imple

Hi Professionals,

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

Mandatory Skills:

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

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

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 Summary

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

Must-Haves:

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

Responsibilities:

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

Must Have Technical/Functional Skills Responsibility of / Expectations from the Role Role Agentic AI Engineer Location New York NJ Exp - 4 Years of Experience in Agentic AI Implementation Key Responsibilities Agent Development Design, code, and test autonomous AI agents that can break down complex tasks, reason through them, and take actions. System Integration Connect agents to databases, APIs, and SaaS platforms to perform real-world actions. Memory Context Management Implement systems (e.g., vector stores) that allow agents to retain memory and understand context over long-running tasks. Multi-Agent Coordination Build frameworks where multiple agents collaborate or negotiate to solve problems. Prompt Engineering Optimization Refine prompts and models to improve reasoning and performance. Required Skills and Qualifications Technical Proficiencies Python, API integration, and experience with LLMs. Frameworks LangChain, LangGraph, and other agent-based architectures. Data Structures Knowledge of vector databases and knowledge bases. Education Bachelors or Masters degree in Computer Science, AI, Mathematics, or a related field TCS Employee Benefits Summary: Discretionary Annual Incentive. Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans. Family Support: Maternal & Parental Leaves. Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement. Time Off: Vacation, Time Off, Sick Leave & Holidays. Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

Salary Range: $100,000 - $120,000 a year

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

Job Title: Agentic AI Engineer

Location: Remote Job (Canada)

Duration: 12 Months+

Job Description:

We re looking for an Agentic AI Developer who lives at the intersection of Python, autonomous systems, and real-world impact.This isn t a train a model and throw it over the wall role you ll design, build, and ship AI agents that think, act, and learn inside real products.

What You ll Do:

Design and build agentic AI systems (planning, reasoning, tool use, memory, feedback loops)Develop and optimize Python-based AI services for production useArchitect multi-agent workflows and autonomous decision pipelinesIntegrate LLMs with APIs, databases, tools, and real-world actionsOwn features end-to-end from concept prototype productionRapidly experiment, measure outcomes, iterate, and improveCollaborate directly with founders, product, and customersMake smart trade-offs between speed, scalability, and correctness

What We re Looking For:

Strong Python skills (clean, readable, production-grade code)Hands-on experience with LLMs, agents, or autonomous workflows

Solid understanding of:

Prompt engineering & evaluationTool/function callingMemory & context managementOrchestration frameworks (Lang Chain, Crew AI, Auto Gen, or similar)Experience deploying AI systems (APIs, async jobs, background workers)Comfort with data stores (SQL/NoSQL/vector DBs)Familiarity with cloud environments (AWS/Google Cloud Platform/Azure is a plus)

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

About Scale AI

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.
Role Overview

As a Forward Deployed AI Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments.

This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows.
Key ResponsibilitiesCustomer Integration & Deployment
• Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements
• Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
• Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
• Deploy and configure AI models and agents within customer security and compliance boundaries
AI Agent Development
• Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
• Architect multi-agent systems that orchestrate between different models, tools, and data sources
• Implement evaluation frameworks to measure agent performance and iterate toward business objectives
• Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement
Prompt Engineering & Optimization
• Create sophistic

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

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

What this role is

We build AI agents that do real work.

Not assistants. Not demos.

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

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

This is not prompt engineering.

This is making AI work in production.

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

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

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

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

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

Important:

LLM experience alone is not enough.

We care about how you make systems reliable.

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

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

Application (required)

1. Project (GitHub)

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

2. Short answer (5–10 sentences)

Describe a system where an AI agent failed.

What caused it, and how would you fix it?

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

We Are

We are entering into a new decade of Data & AI that will reshape work and society. Accenture is stepping boldly into this future with a clear strategy and purpose: to help clients optimize and reinvent their business with data & AI — backed by a $3B investment and commitment to our people to do industry-defining work.

With over 77,000 professionals dedicated to Data & AI, Accenture’s Data & AI organization is powered by experienced innovation, strategic investment, exceptional talent, and our power ecosystem.

You Are

As a Forward Deployed Engineer, you will play a pivotal role in designing, building, and deploying next-generation AI systems powered by Large Language Models (LLMs). You will contribute across the full AI lifecycle — from researching and fine-tuning foundation models to prompt engineering, system integration, and deployment into production environments. You will improve performance, accuracy and alignment of the LLMs and AI systems. You bring a mix of hands-on engineering skills, deep knowledge of modern AI architectures, and a passion for applying AI responsibly to solve real-world problems. In addition, you will utilize your strong skills to develop and integrate AI Systems into products and services. You have expertise in designing, developing, and optimizing AI prompts.

Position Responsibilities:
• Design, develop, and optimize AI prompts and next-generation applications powered by foundation models, including Large Language Models (LLMs).
• Architect and implement generative agent systems using frameworks for multi-model coordination to tackle complex tasks.
• Develop application and component strategies, overseeing both user experience and backend systems.
• Define, evaluate, and optimize AI system architectures, leveraging relevant frameworks and best practices.
• Conduct thorough code reviews, provide expert guidance on enhancements and issue resolution, and ensure adherence to engineering standards.
• Build and maintain scalable ma

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

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

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

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

Must Have Technical/Functional Skills
• Responsibility of / Expectations from the Role
• Role Agentic AI Engineer
• Location New York NJ
• Exp - 4 Years of Experience in Agentic AI Implementation

Key Responsibilities
• Agent Development Design, code, and test autonomous AI agents that can break down complex tasks, reason through them, and take actions.
• System Integration Connect agents to databases, APIs, and SaaS platforms to perform real-world actions.
• Memory Context Management Implement systems (e.g., vector stores) that allow agents to retain memory and understand context over long-running tasks.
• Multi-Agent Coordination Build frameworks where multiple agents collaborate or negotiate to solve problems.
• Prompt Engineering Optimization Refine prompts and models to improve reasoning and performance.

Required Skills and Qualifications
• Technical Proficiencies Python, API integration, and experience with LLMs.
• Frameworks LangChain, LangGraph, and other agent-based architectures.
• Data Structures Knowledge of vector databases and knowledge bases.
• Education Bachelors or Masters degree in Computer Science, AI, Mathematics, or a related field

TCS Employee Benefits Summary:

Discretionary Annual Incentive.

Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.

Family Support: Maternal & Parental Leaves.

Insurance Options: Auto & Home Insurance, Identity Theft Protection.

Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.

Time Off: Vacation, Time Off, Sick Leave & Holidays.

Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

Salary Range: $100,000 - $120,000 a year

Location

Jersey City, NJ

Job Function

TECHNOLOGY

Role

Engineer

Job Id

401620

Desired Skills

Data Structures | Python

Salary Range

$100,000-$120,000 a year

Desired Candidate Profile

Qualifications : BAC

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

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

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

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

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

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

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

The Role:

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

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

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

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

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

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

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?