Senior AI Engineer: GenAI, MLOps & Production Systems

Stanfordlivetickets; Redwood City (CA); On-site; USD 170,000 - 195,000; Full time

Benefits offered by this job

Health benefits

Tuition assistance

Flexible work options

PTO 18+ days per year

401(k)

Mental health programs

Commuter benefits

Job summary

Stanford University invites an experienced AI/GenAI engineer to join its Enterprise Technology team to design, implement, and support AI solutions across university use cases. You will influence strategic direction and architecture for AI‑driven information systems, incorporating new capabilities (LLMs, RAG, agentic frameworks, MLOps) to improve workflow, efficiency, and decision‑making.

You may serve as technical lead for AI tracks and related applications.

Qualifications

• Experience building and shipping at least one production LLM agent or agentic workflow using frameworks such as LangGraph/LangChain/AutoGen or equivalent.
• Proven delivery with 3+ AI/ML projects and 2+ GenAI/LLM projects in production with operational support.
• Strong understanding of AI/ML concepts and experience designing, developing, testing, and deploying AI‑driven applications.
• Proficiency in Python and experience with Node.js/Next.js/React/TypeScript and Java.
• Experience with cloud AI stacks (Google Vertex AI, AWS Bedrock, Azure OpenAI) and vector/search tech (Pinecone, Elastic/OpenSearch, FAISS).
• Knowledge of data design/architecture and relational/NoSQL databases.
• Thorough SDLC, MLOps, and quality control practices.
• Ability to define/solve logical problems for highly technical applications; strong problem‑solving skills.
• Excellent communication and collaboration skills to bridge technical and non‑technical teams.

Responsibilities

• Translate requirements into well‑engineered AI components (pipelines, vector stores, prompt/agent logic).
• Build and maintain LLM‑based agents/services calling enterprise tools via approved APIs.
• Configure and optimize RAG workflows and integrate with search/vector infrastructure.
• Follow and improve CI/CD, testing, and model/versioning practices; own feature delivery from dev to prod.
• Apply guardrails and work with InfoSec to close gaps; document decisions and risks.
• Instrument services with KPIs and build lightweight dashboards.
• Write APIs, workflows, runbooks, and user stories; support UAT activities.
• Mentor junior engineers and lead code reviews and pair programming.

Skills

Agent/agentic framework design

Production AI delivery

AI/ML concepts

Python

Node.js/Next.js/React/TypeScript

Cloud AI stacks

Data design/architecture

SDLC & MLOps

Communication & collaboration

Education

Bachelor's degree + 8 years experience

Tools

LangChain

LangGraph

Vertex AI

Pinecone/Elastic/OpenSearch

Job description

Stanford University invites an experienced AI/GenAI engineer to join its Enterprise Technology team to design, implement, and support AI solutions across university use cases. You will influence strategic direction and architecture for AI‑driven information systems, incorporating new capabilities (LLMs, RAG, agentic frameworks, MLOps) to improve workflow, efficiency, and decision‑making.

You may serve as technical lead for AI tracks and related applications.