Stanford University · 4 months ago
AI Applications Engineer
Redwood City, CA
Full-time
Onsite
Senior Level, Lead/Staff
$170K/yr - $190K/yr
8+ years expStanford University is seeking an experienced AI Applications Engineer to join their Enterprise Technology team. The role involves designing, implementing, and supporting AI solutions for various university use cases, influencing strategic direction and architecture for AI-driven systems, and providing mentorship and thought leadership.
EducationHigher EducationUniversities
Responsibilities
Translate requirements into well-engineered components (pipelines, vector stores, prompt/agent logic, evaluation hooks) and implement them in partnership with the platform/architecture team
Build and maintain LLM-based agents/services that securely call enterprise tools (ServiceNow, Salesforce, Oracle, etc.) using approved APIs and tool-calling frameworks
Configure and optimize RAG workflows (chunking, embeddings, metadata filters) and integrate with existing search/vector infrastructure—escalating architecture changes to designated architects
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
Apply established guardrails (PII redaction, policy checks, access controls). Partner with InfoSec and architects to close gaps; document decisions and risks
Instrument services with KPIs (latency, cost, accuracy/quality) and build lightweight dashboards. Deep BI/reporting not primary
Write clear technical docs (APIs, workflows, runbooks), user stories, and acceptance criteria. Support and sometimes lead UAT/test activities
Facilitate working sessions with stakeholders; mentor junior engineers through code reviews and pair programming; provide concise updates and risk flags
Qualification
Required
Bachelor's degree and eight years of relevant experience or a combination of education and relevant 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
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
One of (or equivalent experience with): Google/AWS/Azure ML/AI certifications or strong demonstrable portfolio of production AI systems
Preferred
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
Benefits
Career development programs
Tuition reimbursement
Generous time-off
Family care resources
Excellent health care benefits
Free commuter programs
Ridesharing incentives
Discounts
Company
Stanford University
Stanford University is a teaching and research university that focuses on graduate programs in law, medicine, education, and business.
10001+ employees
H1B Sponsorship
Stanford University has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2020 (12)
Funding
Current Stage
Late StageTotal Funding
$26.52MKey Investors
National Institutes of HealthCalifornia Institute for Regenerative MedicineGRAMMY Museum
2025-09-08Grant
2025-01-30Grant· $5.6M
2023-08-17Grant
Leadership Team
Nadia Roumani
Co-founder and Senior Designer, Designing for Social Systems (DSS) Program, d.school
Howard Wolf
Vice President for Alumni Affairs
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