Principal Data Scientist

Responsibilities

• Develop LLM-powered automation tools for clinical reporting and document generation workflows
• Build AI-driven code generation pipelines and quality assessment frameworks
• Design and implement human-in-the-loop review workflows with feedback loops to continuously improve output quality
• Design and build multi-agent systems for data workflows — agents that retrieve, generate, validate, and iterate autonomously
• Implement agent orchestration using frameworks such as Google ADK, LangGraph, or LangChain
• Deploy and manage agents on Google Vertex AI
• Use AI coding tools (e.g. Gemini CLI, GitHub Copilot) as a core part of your development workflow
• Critically review and validate AI-generated code — understanding what it produces, why, and when it’s wrong
• Write effective prompts to direct AI tools toward correct, secure, well-structured output
• Know when to use AI and when to write code manually
• Strong Python skills
• Hands-on experience building RAG systems or LLM-powered applications (using LangChain, LlamaIndex, or similar frameworks)
• Experience integrating LLM APIs (Google Gemini, OpenAI, or similar) — we work primarily through Google Vertex AI
• Working knowledge of vector databases (ChromaDB, Weaviate, Qdrant, Pinecone, or similar)
• Docker and containerized deployments
• Comfortable using AI-assisted development tools (e.g. Gemini CLI, GitHub Copilot) — and critically evaluating what they produce