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Metro location and mid-level AI title increase applicant density despite niche pharmacovigilance specialization.
Strong pharmacovigilance and regulatory domain requirements make industry-specific experience highly important.
Explicit 3+ years, mandatory LLM experience, Python and AWS requirements enforce strict shortlisting.
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Design and implement specialized pharmacovigilance AI agents for processing and analyzing adverse event data.
Build, iterate, and optimize prompt chains and deterministic rule engines for tasks like parsing, extraction, coding, causality assessment, and E2B output generation.
Develop evaluation datasets, run benchmarks, implement quality control logic, and build human-in-the-loop feedback systems to improve AI agent performance.
3+ years software engineering experience with at least 1 year working on LLM API applications (Anthropic, OpenAI, or equivalent).
Proficient in Python with production-level coding experience.
Experience building and evaluating NLP or LLM-based systems using measurable quality metrics.
Bachelor's degree in computer science or related field, or equivalent professional experience.
Experienced in prompt engineering and LLM orchestration frameworks (e.g., LangChain, LangGraph).
Comfortable integrating AI systems with AWS services (S3, Lambda, IAM) and managing secure API/tool integrations.
Background in medical or clinical NLP, pharmacovigilance domain knowledge, or experience in pharma/biotech/clinical research environments.