AI Lead

Role Overview

The AI Lead/ Architect 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

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.