AI Applications Engineer

Stanford University • Redwood City, CA

1d

About The Position

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.).

Requirements

• Bachelor's degree and five years of relevant experience, or a combination of education and relevant experience.
• 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.

Nice To Haves

• 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.

Responsibilities

• 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.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level