AI Engineer, Agent/Platform Tracks

Key Responsibilities

• Implement the specialized pharmacovigilance agents: write system prompts, configure model parameters, build tool-use definitions, and define agent boundaries to ensure precise adverse event processing
• Build and iterate prompt chains for each processing step: source document parsing, field extraction, MedDRA coding suggestions, causality assessment logic, narrative drafting, and E2B(R3) output generation
• Develop the deterministic rule engine layer: implement ICH E2B field validation checks, MedDRA hierarchy verification, and regulatory logic constraints that operate alongside LLM outputs
• Create and maintain evaluation datasets in collaboration with the pharmacovigilance domain team: annotated ground-truth cases, edge case libraries, and regression test suites
• Develop and maintain Model Context Protocol (MCP) servers to expose enterprise applications, APIs, databases, and services as standardized tools for AI agents
• Implement secure MCP integrations, tool definitions, authentication, and testing to enable reliable agent interaction with internal and external systems
• Run accuracy benchmarks, analyze failure modes, and iterate on prompts and agent configurations to improve performance against defined thresholds
• Implement the quality control agent's cross-verification logic: configure separate Claude instances, build comparison algorithms, and calibrate confidence scoring
• Build human-in-the-loop feedback mechanisms: reviewer interfaces for accept/modify/reject decisions, structured feedback capture, and feedback-to-prompt-improvement pipelines

You'll thrive in this role if you bring