Director Engineering - AI/ML

About this role

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Day - 08 Hour (United States of America)

This is a Stanford Health Care job.

We are looking for a rare combination of hands-on technical leader and strategic thinker to own the engineering vision for chatEHR as we mature from a pilot into a tier 1 clinical platform. This is not a role for someone who manages from a distance -- you will need the credibility to earn the respect of a talented engineering team, the organizational savvy to navigate a complex health system, and the vision to bridge cutting-edge research with real-world clinical application.

You will be responsible for building the infrastructure, environments, and engineering discipline that transforms chatEHR into a reliable, scalable platform trusted by thousands of clinicians -- while staying ahead of a fast-moving AI landscape.

If you are energized by the intersection of pioneering research and production-grade systems, and you know how to shepherd ambitious ideas into operational reality, this role was built for you.

A Brief Overview Stanford Health Care and the Stanford School of Medicine are at the forefront of the AI revolution in healthcare. We are building chatEHR, a secure, compliant, and powerful Generative AI platform designed to transform healthcare delivery, accelerate medical research, and improve patient outcomes.

We are seeking a hands-on, visionary Director of Engineering to lead the technical development and strategic execution of the chatEHR platform. This is a unique opportunity to build and scale a team that sits at the intersection of pioneering AI research and real-world clinical application. You will be responsible for building the core platform, agentic frameworks, and user-facing applications that will be used by thousands of clinicians, researchers, and staff.

Locations Stanford Health Care

What you will do • Leadership & Strategy • Build & Mentor: Recruit, lead, and mentor a high-performing team of software engineers and data scientists, fostering a culture of innovation, collaboration, and technical excellence. • Define the Vision: Partner with clinical and product leadership to develop and execute a strategic technical roadmap for the chatEHR platform, aligning with organizational goals. • Ensure Compliance & Ethics: Serve as the key engineering leader responsible for ensuring all AI applications adhere to strict healthcare regulations (HIPAA), data privacy laws, and ethical AI standards. • Technical Delivery & Execution • Platform Architecture: Oversee the architecture and design of a scalable, secure, and reliable GenAI platform, ensuring robust integration with existing EHR systems and clinical workflows. • Agentic Frameworks: Lead the design and development of a sophisticated agentic framework for Stanford Healthcare, enabling rapid creation and deployment of new AI-powered workflows. • API & Application Development: Manage the development of user-facing chatEHR applications and publish a comprehensive set of platform APIs for enterprise-wide consumption. • Release Management: Manage multiple concurrent development streams and releases, ensuring timely delivery and high-quality standards for the entire platform. • Modern MLOps: Implement and oversee robust MLOps practices, including state-of-the-art GenAI evaluation techniques in collaboration with the Chief Data Science Officer and the members of the GUIDE-AI lab ([Link to arXiv paper]). • Collaboration • Bridge Research & Practice: Act as the primary technical liaison between your engineering team and partners in the Chief Data Science Officer's lab, translating novel research into production-ready platform features. • Engage Stakeholders: Work closely with cross-functional teams—including product management, user success, clinical staff, and researchers—to identify and prioritize high-impact opportunities for GenAI.

Education Qualifications • 10+ years of experience in software engineering, with at least 5+ years in a senior leadership role (Manager, Senior Manager, or Director) managing software development teams. • Proven track record of leading teams that have successfully built, deployed, and scaled AI/ML products. • Deep technical knowledge of the modern GenAI stack, including LLMs, retrieval-augmented generation (RAG), vector databases, and agentic frameworks. • Expertise in designing and building scalable, cloud-native systems (GCP, AWS, or Azure) and container orchestration (Kubernetes). • Strong experience with API design, microservices architecture, CI/CD, and MLOps principles. • Exceptional ability to mentor engineers, set technical direction, and manage complex projects with multiple stakeholders. • Outstanding communication and interpersonal skills, with the ability to articulate complex technical concepts to non-technical and clinical audiences.

Experience Qualifications • BS or MS in Computer Science, AI, or a related engineering field. Required • PhD in Computer Science, AI, or a related field. Preferred

Preferred Knowledge, Skills and Abilities • Direct experience in the healthcare, biotech, or life sciences industry, particularly with standards like HIPAA, FHIR, or GxP. • Experience building applications on top of Electronic Health Record (EHR) systems like Epic. • A portfolio of published research in AI/ML or contributions to major open-source projects.

These principles apply to ALL employees:

SHC Commitment to Providing an Exceptional Patient & Family Experience

Stanford Health Care sets a high standard for delivering value and an exceptional experience for our patients and families. Candidates for employment and existing employees must adopt and execute C-I-CARE standards for all of patients, families and towards each other. C-I-CARE is the foundation of Stanford’s patient-experience and represents a framework for patien

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