Develop and lead enterprise AI engineering solutions, including Python tooling, RAG systems, LLM agent workflows, vector database integrations, and AI platform connectors. Administer AWS Bedrock, evaluate models using MMLU and TruthfulQA, establish prompt engineering and model versioning standards, and provide technical leadership for scalable AI data systems. Collaborate with product and domain teams to deploy AI-enabled products, define roadmaps, and monitor system effectiveness.

Owns the end-to-end architecture and deployment of agentic AI systems using Claude and AWS. Responsibilities include agent orchestration, AI infrastructure, evaluation pipelines, risk safeguards, audit logging, human-in-the-loop workflows, and production operations. The role mentors engineers, establishes engineering standards, and requires Python, SQL, distributed systems, cloud infrastructure, Docker, CI/CD, and LLM application experience in a regulated environment.