Senior AI Engineer

Design, build, and deploy clinical AI agents that reason over patient context, invoke tools, and generate care recommendations.

Own reliability, observability, and cost efficiency of LLM-powered workflows at scale.

Build and optimize RAG pipelines over clinical knowledge bases, treatment protocols, and real-time patient data.

Develop evaluation frameworks: offline benchmarks, safety tests, regression suites, and LLM-as-judge pipelines wired into CI/CD.

Design multi-step agent orchestration: planning, memory, tool use, error recovery, and human-in-the-loop escalation paths.

Collaborate with clinical, product, and engineering teams to translate patient care needs into AI system design.

Stay at the forefront of AI and engineering best practices, continuously pushing the team to raise the bar on quality, performance, and architecture.

Bachelor's or Master’s degree in Computer Science, Engineering or related field, or equivalent work experience

5+ years of software engineering experience, with 2+ years building AI/ML-powered systems in production

Hands-on experience with LLM APIs (OpenAI, Anthropic, open-source models) including prompt engineering, tool use / function calling, and structured outputs

Experience building RAG systems: embeddings, vector stores, retrieval optimization, and grounding

Experience in a high-growth, fast-paced environment with end-to-end ownership from design through production

Experience with agent frameworks or orchestration patterns (tool calling, planners, multi-agent coordination)