Owns AI foundation for generative AI in mental healthcare, architecting production-grade systems like RAG and agentic loops while ensuring technical excellence and safety in regulated environments. Requires 10+ years software engineering, AI/ML expertise, and cloud/distributed systems experience.
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About the role
Required Qualifications
10+ years of software engineering experience, including 7+ years with Public Cloud (AWS, GCP, etc.) and 5+ years designing/scaling distributed systems.
5+ years of deep experience in Python and at least one other backend language (TypeScript, Java, Go, etc.).
2+ years building AI-powered products at scale with foundation models (OpenAI, Anthropic, Gemini, etc.).
2+ years of experience with LLM integration patterns such as RAG, agentic loops, and orchestration frameworks like LangChain or LlamaIndex.
3+ years working with MLOps, data pipelines, evaluation, and observability systems for continuous model improvement.
Preferred Qualifications
Experience architecting secure, compliant AI solutions in regulated environments (HIPAA, GDPR).
Familiarity with human-in-the-loop systems and clinical decision support frameworks.
Experience designing evaluation pipelines for human alignment, factual accuracy, or model interpretability.
Contributions to open-source AI frameworks or applied research in GenAI safety.
Experience leading or mentoring engineering teams in AI or ML platform domains.
Lead technical vision and execution for post-training systems that transform foundation models into intelligent, engaging products. Drive alignment algorithms, RL, and infrastructure for large-scale LLM training and serving.
275k – 400k/yr
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