Stanford University
Overview
AI Applications Engineer — Business Affairs: University IT (UIT), Redwood City, California, United States. Information Technology Services. Post Date Sep 08, 2025. Requisition #107213. Job Purpose: 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, prototyping and productionizing—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.
Education & Experience Bachelor's degree and eight years of 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, and 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 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.
Pay and Benefits The expected pay range for this position is $169,728 to $190,000 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered will be determined based on factors such as the scope and responsibilities of the position, qualifications, budget, internal equity, location, and market.
Base pay is one aspect of the rewards package. The Cardinal at Work website provides detailed information on benefits and rewards. Specifics may be discussed during the hiring process.
Why Stanford is for You
Freedom to grow:
Career development programs, tuition reimbursement, or auditing a course; visiting talks and events.
A caring culture:
Retirement plans, time off, and family care resources.
A healthier you:
Health and fitness resources and comprehensive health care benefits.
Discovery and fun:
Access to museums, trails, and cultural experiences.
Enviable resources:
Commute programs, incentives, and discounts.
Redwood City:
Stanford Redwood City campus amenities and facilities.
The job duties listed are typical examples and may vary. Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
Additional Information
Schedule: Full-time
Job Code: 4823
Employee Status: Regular
Grade: L
Requisition ID: 107213
Work Arrangement: Hybrid Eligible
#J-18808-Ljbffr
AI Applications Engineer — Business Affairs: University IT (UIT), Redwood City, California, United States. Information Technology Services. Post Date Sep 08, 2025. Requisition #107213. Job Purpose: 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, prototyping and productionizing—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.
Education & Experience Bachelor's degree and eight years of 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, and 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 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.
Pay and Benefits The expected pay range for this position is $169,728 to $190,000 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered will be determined based on factors such as the scope and responsibilities of the position, qualifications, budget, internal equity, location, and market.
Base pay is one aspect of the rewards package. The Cardinal at Work website provides detailed information on benefits and rewards. Specifics may be discussed during the hiring process.
Why Stanford is for You
Freedom to grow:
Career development programs, tuition reimbursement, or auditing a course; visiting talks and events.
A caring culture:
Retirement plans, time off, and family care resources.
A healthier you:
Health and fitness resources and comprehensive health care benefits.
Discovery and fun:
Access to museums, trails, and cultural experiences.
Enviable resources:
Commute programs, incentives, and discounts.
Redwood City:
Stanford Redwood City campus amenities and facilities.
The job duties listed are typical examples and may vary. Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.
Additional Information
Schedule: Full-time
Job Code: 4823
Employee Status: Regular
Grade: L
Requisition ID: 107213
Work Arrangement: Hybrid Eligible
#J-18808-Ljbffr