GenAI Systems Engineer - Production AI Lead

Stanford University School of Medicine; Redwood City (CA); On-site; USD 170,000 - 195,000; Full time

Job summary

Stanford University School of Medicine is seeking an experienced AI/GenAI engineer to design, implement, and support AI solutions across university use cases. You will influence strategy and architecture for AI-driven information systems, incorporating LLMs, RAG, and MLOps to improve workflow, efficiency, and decision-making.

You may lead specific AI tracks and mentor others. This role blends hands-on engineering with mentorship and thought leadership, prototyping and productionizing solutions,

Qualifications

• Agent/Agentic Framework Experience: Built and shipped at least one production LLM agent or agentic workflow using frameworks such as LangGraph, LangChain, CrewAI/AutoGen, Google Agent Builder/Vertex AI Agents (or equivalent).
• Proven Delivery: Implemented 3+ AI/ML projects and 2+ GenAI/LLM projects in production with operational support.
• Strong understanding of AI/ML concepts (LLMs/transformers and classical ML) and experience designing, developing, testing, and deploying AI-driven applications.

Responsibilities

• Translate requirements into well-engineered components (pipelines, vector stores, prompt/agent logic) and implement them in partnership with the platform/architecture team.
• Build and maintain LLM-based agents/services that securely call enterprise tools using approved APIs and tool-calling frameworks.
• Configure and optimize RAG workflows and integrate with existing search/vector infrastructure.

Education

Bachelor's degree and eight years relevant experience

Job description

Stanford University School of Medicine is seeking an experienced AI/GenAI engineer to design, implement, and support AI solutions across university use cases. You will influence strategy and architecture for AI-driven information systems, incorporating LLMs, RAG, and MLOps to improve workflow, efficiency, and decision-making.

You may lead specific AI tracks and mentor others. This role blends hands-on engineering with mentorship and thought leadership, prototyping and productionizing solutions,