Enterprise GenAI Engineer — LLMs, RAG & MLOps

Stanford University; Palo Alto (CA); On-site; USD 169,728 - 194,585; Full time

Job summary

Stanford University’s Enterprise Technology team seeks an experienced AI/GenAI engineer to design, implement, and support AI solutions across university use cases. You will influence requirements, architecture, and workflows for AI-driven information systems.

The role blends hands-on engineering with mentorship and thought leadership: prototype and productionize solutions, present proofs of concept, and lead AI tracks while partnering with project managers, security, and app teams (ServiceNow,

Qualifications

• Agent/agentic framework experience with production LLM agents or workflows.
• 3+ AI/ML projects in production with operational support.
• Strong understanding of AI/ML concepts (LLMs/transformers; traditional ML).
• Proficient in Python; comfortable with Node.js/Next.js/React/TypeScript and Java.
• Experience with cloud AI stacks and vector/search technologies.
• Knowledge of data design/architecture and databases.
• Solid SDLC and MLOps understanding; quality control practices.
• Strong problem-solving and communication skills.

Responsibilities

• AI/ML System Implementation & Integration: translate requirements into engineered components and deploy with platform/architecture team.
• Application & Agent Development: build/maintain LLM-based agents calling enterprise tools via approved APIs.
• RAG & Search Enablement: configure/optimize RAG workflows and integrate with vector/search infra.
• MLOps & SDLC Practices: follow CI/CD, testing, versioning; manage feature delivery across environments.
• Governance, Security & Compliance: apply guardrails; partner with InfoSec; document decisions/risks.
• Metrics & Reporting: instrument services with KPIs; build lightweight dashboards.
• Documentation & Communication: write APIs/runbooks/user stories; support UAT/test activities.
• Collaboration & Mentorship: lead sessions; mentor engineers through code reviews.

Skills

Agent/agentic framework experience

Production AI/ML delivery

AI/ML concepts (LLMs)

Python

Cloud AI stacks

Data architecture

SDLC & MLOps

Communication & collaboration

Education

Bachelor's degree + 8 years experience

Tools

LangGraph/LangChain

Pinecone/Elastic/OpenSearch

Vertex AI / SageMaker

Job description

Stanford University’s Enterprise Technology team seeks an experienced AI/GenAI engineer to design, implement, and support AI solutions across university use cases. You will influence requirements, architecture, and workflows for AI-driven information systems.

The role blends hands-on engineering with mentorship and thought leadership: prototype and productionize solutions, present proofs of concept, and lead AI tracks while partnering with project managers, security, and app teams (ServiceNow,