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Specialized Agentic LLM and life-sciences requirements plus seniority limit candidate pool despite employer brand.
Requires deep LLM, Langfuse, and life-sciences regulatory experience, making cross-industry transfer difficult.
Multiple explicit 8+ year mandates and specialized GenAI, AWS Bedrock, and GxP requirements enforce strict filters.
Design and develop agent-based AI solutions for clinical, regulatory, and enterprise workflows using LLMs, RAG, and multi-agent architectures.
Build reusable AI platform components including prompt orchestration layers, agent execution frameworks, and data ingestion pipelines to enable scalable, multi-tenant enterprise use.
Develop backend APIs with Python and FastAPI, integrate AWS Bedrock for LLM provisioning, ensure observability with Langfuse, and align solutions with enterprise architecture and governance standards.
7+ years of strong Python engineering experience.
8+ years of experience in FastAPI/backend API development and building LLM/Generative AI production solutions.
Familiarity with AWS Bedrock or equivalent GenAI platforms and Langfuse or LLM observability tools.
Bachelor’s degree in Computer Science, Engineering, or a related field.
Experienced in agentic AI and AI platform development for enterprise, especially in clinical, regulatory, or life sciences domains.
Comfortable with integrating AI solutions into scalable cloud environments using AWS services like EKS, Lambda, and API Gateway.
Skilled in end-to-end development including backend engineering, full stack (React/Next.js), observability, and enterprise-grade security and governance compliance.