AI Engineer
Location: Redwood City, CA, United States · Reference: 109149
Are you an experienced AI/GenAI engineer who loves shipping real systems? Join
Stanford's Enterprise Technology team to design, implement, and support AI
solutions across university use cases. In this role, you will influence
strategic direction requirements 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
the technical lead for specific AI tracks and interrelated applications.
This role blends hands-on engineering with mentorship and thought leadership.
You will prototype and productionize—presenting proofs of concept, demoing
solutions to stakeholders, and partnering with project managers, technical
managers, architects, security, infrastructure, and application teams
(ServiceNow, Salesforce, Oracle Financials, etc.)
Core Duties :
AI/ML System Implementation & Integration: Translate requirements into
well-engineered components (pipelines, vector stores, prompt/agent logic,
evaluation hooks) and implement them in partnership with the
platform/architecture team.
Application & Agent Development: Build and maintain LLM-based
agents/services that securely call enterprise tools (ServiceNow,
Salesforce, Oracle, etc.) using approved APIs and tool-calling
frameworks. Create lightweight internal SDKs/utilities where needed.
RAG & Search Enablement: Configure and optimize RAG workflows (chunking,
embeddings, metadata filters) and integrate with existing search/vector
infrastructure—escalating architecture changes to designated architects.
MLOps & SDLC Practices: Follow and improve team standards for CI/CD,
testing, prompt/model versioning, and observability. Own feature delivery
through dev/test/prod, coordinating with release managers.
Governance, Security & Compliance: Apply established guardrails (PII
redaction, policy checks, access controls). Partner with InfoSec and
architects to close gaps; document decisions and risks.
Metrics & Reporting: Instrument services with KPIs (latency, cost,
accuracy/quality) and build lightweight dashboards. Deep BI/reporting not
primary.
Documentation & Communication: Write clear technical docs (APIs,
workflows, runbooks), user stories, and acceptance criteria. Support and
sometimes lead UAT/test activities.
Collaboration & Mentorship: Facilitate working sessions with stakeholders;
mentor junior engineers through code reviews and pair programming; provide
concise updates and risk flags.
Qualifications:
Education & Experience:
Bachelor's degree and eight years relevant experience, or a combination of
education and relevant experience.
Required Knowledge, Skills, and Abilities :
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). Able to explain tool selection, orchestration
logic, and post‑deployment support.
Proven Delivery: Implemented 3+ AI/ML projects and 2+ GenAI/LLM projects
in production, with operational support (monitoring, tuning, incident
response). Projects should serve sizable user populations and demonstrate
measurable efficiency gains.
Strong understanding of AI/ML concepts (LLMs/transformers and classical
ML) and experience designing, developing, testing, and deploying AI-
driven applications.
Programming Expertise: Python (primary) plus experience with
Node.js/Next.js/React/TypeScript and Java; demonstrated ability to quickly
learn new tools/frameworks.
Experience with cloud AI stacks (e.g., Google Vertex AI, AWS Bedrock,
Azure OpenAI) and vector/search technologies (Pinecone,
Elastic/OpenSearch, FAISS, Milvus, etc.).
Knowledge of data design/architecture, relational and NoSQL databases, and
data modeling.
Thorough understanding of SDLC, MLOps, and quality control practices.
Ability to define/solve logical problems for highly technical
applications; strong problem-solving and systematic troubleshooting
skills.
Excellent communication, listening, negotiation, and conflict resolution
skills; ability to bridge functional and technical resources.
Desired Knowledge, Skills, and Abilities :
MLOps Tooling: MLflow, Kubeflow, Vertex Pipelines, SageMaker Pipelines;
LangSmith/PromptLayer/Weights & Biases.
Open Source Savvy: Experience working with, customizing, and improving
open-source solutions; comfortable contributing fixes/features upstream.
Rapid Tech Adoption: Demonstrated ability to pick up a new
technology/framework quickly and deliver production value with it.
GenAI Frameworks: LangChain, LlamaIndex, DSPy, Haystack, LangGraph, Agent
Engine, Google ADK, AWS AgentCore, CrewAI/AutoGen.
Security & Governance: Implementing AI guardrails, red-teaming, policy
enforcement frameworks.
Enterprise Integrations: ServiceNow, Salesforce, Oracle Financials or
others.
UI Development: React/Next.js/Tailwind for internal tools.
Prompt engineering at scale: Structured prompts (JSON/function-calling),
templates, version control; automated/offline & online evals (rubrics,
hallucination/bias checks, A/B tests, golden sets).
Parameter‑efficient fine‑tuning (LoRA/QLoRA/adapters), supervised
instruction tuning; hosting open‑weight models (Llama/Mistral/Qwen) with
vLLM/TGI/Ollama.
Safety/guardrails frameworks (Guardrails.ai, NeMo Guardrails, Azure/AWS
safety filters) and jailbreak/drift detection.
Hybrid search & reranking (BM25+dense, Cohere/Voyage/Jina rerankers),
synthetic data generation, provenance/watermarking.
Telemetry & governance: prompt/model drift monitoring, policy‑as‑code,
audit logging, red‑teaming playbooks.
Certifications and Licenses :
Required: One of (or equivalent experience with): Google/AWS/Azure ML/AI
certifications or strong demonstrable portfolio of production AI systems.
Physical Requirements :
Constantly perform desk-based computer tasks.
Frequently sit, grasp lightly/fine manipulation.
Occasionally stand/walk, writing by hand.
Rarely use a telephone, lift/carry/push/pull objects that weigh up to 10
pounds.
Consistent with its obligations under the law, the University will provide
reasonable accommodations to applicants and employees with disabilities.
Applicants requiring a reasonable accommodation for any part of the
application or hiring process should contact Stanford University Human
Resources by submitting a contact form.
Working Conditions :
May work extended hours, evenings, and weekends.
Work Standards :
Interpersonal Skills: Demonstrates the ability to work well with Stanford
colleagues and clients and with external organizations.
Promote Culture of Safety: Demonstrates commitment to personal
responsibility and value for safety; communicates safety concerns; uses
and promotes safe behaviors based on training and lessons learned.
Subject to and expected to stay in sync with all applicable University
policies and procedures, including but not limited to the personnel
policies and other policies found in Stanford's Administrative Guide,
https:// adminguide.stanford.edu.
The expected pay range for this position is $169,728 to $194,585 per
annum.
Stanford University provides pay ranges representing its good faith estimate
of the salary or hourly wage the university reasonably expects to pay for a
position upon hire. The pay offered to a selected candidate will be determined
based on factors such as (but not limited to) the scope and responsibilities
of the position, the qualifications of the selected candidate, departmental
budget availability, internal equity, geographic location and external market
pay for comparable jobs.
At Stanford University, base pay represents only one aspect of the
comprehensive rewards package. The Cardinal at Work website
(https: // cardinalatwork.stanford.edu/benefits-rewards) provides
detailed information on Stanford's extensive range of benefits and rewards
offered to employees. Specifics about the rewards package for this position
may be discussed during the hiring process.
Why Stanford is for you :
Imagine a world without search engines or social platforms. Consider lives
saved through first-ever organ transplants and research to cure illnesses.
Stanford University has revolutionized the way we live and enrich the world.
Supporting this mission is our diverse and dedicated 17,000 staff. We seek
talent driven to impact the future of our legacy. Our culture and unique perks
empower you with:
Freedom to grow. We offer career development programs, tuition
reimbursement, or audit a course. Join a TedTalk, film screening, or
listen to a renowned author or global leader speak.
A caring culture. We provide superb retirement plans, generous time-
off, and family care resources.
A healthier you. Climb our rock wall, or choose from hundreds of
health or fitness classes at our world-class exercise facilities. We also
provide excellent health care benefits.
Discovery and fun. Stroll through historic sculptures, trails, and
museums.
Enviable resources. Enjoy free commuter programs, ridesharing
incentives, discounts and more!
The job duties listed are typical examples of work performed by positions in
this job classification and are not designed to contain or be interpreted as a
comprehensive inventory of all duties, tasks, and responsibilities. Specific
duties and responsibilities may vary depending on department or program needs
without changing the general nature and scope of the job or level of
responsibility. Employees may also perform other duties as assigned.
Stanford is an equal employment opportunity and affirmative action employer.
All qualified applicants will receive consideration for employment without
regard to race, color, religion, sex, sexual orientation, gender identity,
national origin, disability, protected veteran status, or any other
characteristic protected by law.
