Responsibilities

• Design, build, and ship AI systems including architecture, retrieval pipelines, prompts, and deployment
• Implement production-grade Retrieval-Augmented Generation (RAG) systems on AWS infrastructure
• Build and maintain evaluation harnesses for AI systems, including accuracy and hallucination detection
• Design integrations between AI systems and enterprise systems using Model Context Protocol (MCP) and APIs
• Own and maintain LLM security controls, including guardrails and sensitive data redaction
• Develop and maintain AI agents for use in regulated life sciences environments
• Establish modern engineering practices including CI/CD, version control, and environment separation
• Conduct technical evaluations of AI vendors and Foundation Models
• Author technical documentation including architecture diagrams and validation deliverables
• Mentor junior engineers on AI projects...