NEWPosted 3 hours ago
Job ID: JOB_ID_8965
Key Responsibilities
Delivery & Architecture
- Own end-to-end delivery of AI-native programs – from architecture through production deployment
- Design and build multi-agent orchestration systems using LangChain, LangGraph, CrewAI, or equivalent
- Integrate agent systems with enterprise surfaces: APIs, ERPs, CRMs, data platforms – not toy datasets
- Define agent topology: tool routing, memory strategy, state machines, fallback handling
Agentic Coding & Development
- Run agentic coding workflows using Claude Code, Cursor, OpenAI Codex, or equivalent CLI tools
- Lead projects where AI writes significant portions of the codebase – and you guide, review, and ship it
- Work with CLAUDE.md, shared context frameworks, and multi-session agent setups for team use
- Debug non-deterministic agent outputs systematically – not by gut feel
- Translate business problems into agent architectures for global CXO-level stakeholders
- Run discovery workshops, solution reviews, and delivery cadences with client teams
- Prepare and present technical proposals, POC plans, and roadmaps – own the story end-to-end
Team & Practice
- Mentor junior AI engineers; raise AI engineering quality across the delivery team
- Stay current: evaluate new models, frameworks, and tooling before the hype catches up
- Contribute to internal knowledge bases, reusable frameworks, and accelerators
Skills
Agent Orchestration
- LangChain, LangGraph, CrewAI – not just conceptual
Agentic Coding Tools
- Claude Code CLI, Cursor, OpenAI Codex, Copilot
RAG & Vector Stores
- Chroma, Weaviate, Pinecone – knows where RAG breaks
LLM APIs & SDKs
- Anthropic, OpenAI, Gemini – prompt design, tool use
Python / TypeScript
- Primary languages for agent + backend development
LangSmith / Observability
- Tracing, evaluation, debugging agent runs
Cloud Platforms
- Azure, AWS, GCP (at least one) – deployment, infra, managed services
API & System Integration
- REST, gRPC, Kafka – enterprise integration patterns
MCP / Shared Context
- Model Context Protocol, CLAUDE.md, Beads
Agent Evaluation
- Testing non-deterministic outputs, guardrails, evals
CI/CD & DevOps
- Git, containers, pipelines – agents need to ship
- Can present architecture to a CXO without jargon
What You Must Have Actually Done
Not just what you know. What you have shipped.
- Deployed 23 agent-based systems in production – stateful, multi-step, real users
- Used LangGraph for multi-agent orchestration with memory, tool routing, and state management
- Built projects where AI (Claude Code, Codex, Cursor) wrote significant portions of the code
- Implemented RAG pipelines end-to-end – chunking, embedding, retrieval, re-ranking, evaluation
- Integrated agents with real enterprise APIs – not just OpenAI playground or sample data
- Debugged a production agent failure – and fixed it without blaming the model
- Can articulate when NOT to use agents – that is how we know you have built things
Bonus – Real Differentiators
- Experience with Claude Code CLI in team environments (CLAUDE.md, shared context, multi-session flows)
- Familiarity with LangSmith for agent tracing, evaluation pipelines, and debugging at scale
- Has shipped something using MCP (Model Context Protocol) or similar shared-context tooling
- QA/testing mindset for agents – systematic evaluation of non-deterministic outputs
- Background in IT services or consulting – managing client expectations while building
- Experience with SLMs, fine-tuning, or on-device/edge agent deployment
What We Are Not Looking For
- Someone who lists LLMs on a resume but has only called the API in a Jupyter notebook
- AI enthusiasts whose hands-on experience is less than a year old
- People who explain everything in terms of frameworks they have never deployed
- Consultants who can only narrate what others have built
Compensation & Location
Salary: $120,000 – $180,000 per year (Estimated)
Location: New York, NY
Recruiter / Company – Contact Information
Recruiter / Employer: HMG America LLC
Email: sanjeev@hmgamerica.com
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