Agentic AI Lead – Delivery & Engineering
Job Location:
New York City, NY - USA
Monthly Salary:
Posted:
Application Deadline:
Vacancies:
Job Summary
Claude Agentic AI Lead Delivery & Engineering
NYC NY (3 days onsite)
Contract to Hire
Job Description:
About the Role:
This is not a slide-making or prompt-engineering role. We are looking for someone who has built multi-agent AI systems that run in production - not demos not pilots that died after a sprint. You will anchor AI delivery programs end-to-end work directly with global clients and stay sharp on a field that changes every few weeks.
You will report into and replicate the function of a senior AI delivery leader - which means you need both the depth to architect solutions and the presence to walk a CXO through what you built and why it works.
What You Must Have Actually Done
Not just what you know. What you have shipped.
- Deployed 2 3 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 ( 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
