Role Overview :

The AI Lead owns technical architecture and delivery for the agentic pilot. This person selects the target use case with the client, architects the end-to-end agentic solution, sets the observability strategy, and turns pilot results into a repeatable sizing model. The AI Lead also directs identification and sequencing of the next wave of agentic candidate use cases.

Key Responsibilities :

- Lead selection and scoping of the target use case in partnership with client stakeholders and the Data Engineer

- Architect the end-to-end agentic pipeline, including orchestration (LangGraph), retrieval (RAG), and tool/API integration

- Define and stand up an architect-level agent observability strategy: tracing, evaluation harnesses, guardrail and drift monitoring

- Direct and review the work of the AI Engineers, Data Engineer, and QA Engineer across the pilot build

- Design the methodology for measuring FTE efficiency gained from the pilot, in collaboration with QA

- Translate pilot results into a reusable estimation model for sizing future BOWs of a similar project archetype

- Lead identification of 3 - 5 additional agentic candidate use cases and develop a recommended build roadmap and sequencing

- Present pilot outcomes, the estimation model, and the roadmap to client leadership

Required Skills & Experience:

- Deep expertise in LangChain / LangGraph and RAG architecture patterns

- Strong, hands-on Python for agentic application development

- Architect-level experience designing observability/monitoring for agentic or LLM-based systems

- Working knowledge of FastAPI for service/API layer design

- Prior experience scoping and delivering AI/agentic pilots in a consulting context

- Strong client-facing communication and executive presentation skills