Product Engineer - AI/ML

Stanford Health Care • Palo Alto, CA

1d

About The Position

The Product Engineer – AI/ML bridges technical strategy, hands-on software development, and applied AI delivery. In a forward-deployed capacity, the role works directly with operational and clinical stakeholders to identify root challenges, prototype solutions, and build high-value AI capabilities. The position owns end-to-end execution, including writing production-capable code, configuring AI model workflows such as RAG and foundation APIs, and driving initial 0→1 implementation. Working with Data Scientists and Core Platform Engineering, the role helps ensure AI solutions deliver measurable impact.

The Product Engineer evaluates operational needs and technical tradeoffs, integrates prototypes with health system data and workflow tools, and collaborates on testing, evaluation, privacy, and governance. Validated prototypes are transitioned to enterprise-grade platforms in partnership with Data and Software Engineers.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or a related quantitative field, or equivalent practical experience.
• 3–5+ years of progressive experience in data science, software engineering, applied AI engineering, or technical product development.
• Experience working in healthcare, health tech, or complex regulated enterprise environments.
• Excellent communication, interpersonal, problem-solving, and analytical skills.
• Knowledge and understanding of healthcare informatics technologies and standards.
• Ability to manage complex projects with multiple stakeholders and competing priorities.

Nice To Haves

• Master’s degree.
• Proficiency in Python and SQL; experience with REST APIs, web services, and modern development workflows.
• Hands-on experience with foundation model APIs, Retrieval-Augmented Generation (RAG), vector databases, and AI orchestration frameworks.
• Familiarity with enterprise data structures, cloud data platforms, and data privacy governance.
• Ability to analyze operational workflows, probe for root causes, and translate business needs into technical solutions.

Responsibilities

• Partner with operational and clinical teams to identify root-cause challenges.
• Design, build, and iterate on prototypes using programming languages such as Python, modern APIs, LLM orchestration frameworks, and retrieval systems.
• Assess operational bottlenecks and select an appropriate approach, including automation, rule-based logic, or generative AI.
• Balance model accuracy, execution latency, maintainability, and operational inference costs.
• Integrate prototypes with health system data stores, enterprise APIs, and operational workflow tools.
• Collaborate with Data Science teammates to submit solutions to formal evaluation harnesses before enterprise deployment.
• Help construct test suites to measure and mitigate model hallucinations, errors of omission, and factual inaccuracies.
• Ensure alignment with healthcare data privacy policies, HIPAA regulations, and institutional AI governance standards.
• Partner with Data and Software Engineers to transition validated prototypes to enterprise-grade platforms.

What This Job Offers

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