Director Engineering - AI/ML at Stanford Health Care

Palo Alto, California, United States -

Full Time

Start Date

Immediate

Expiry Date

26 Jun, 26

Salary

148.91

Posted On

28 Mar, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI/ML, Engineering Leadership, Technical Vision, Strategic Roadmap, HIPAA Compliance, GenAI Platform, Agentic Frameworks, API Development, MLOps, Cloud-Native Systems, Kubernetes, RAG, Vector Databases, Mentoring, Stakeholder Engagement, EHR Integration

Industry

Hospitals and Health Care

Description

1.0 FTE Full time Day - 08 Hour R2654777 Hybrid 108480039 TDS Data Science Innovation Technology & Digital Solutions PALO ALTO, 1830 Embarcadero, California If you're ready to be part of our legacy of hope and innovation, we encourage you to take the first step and explore our current job openings. Your best is waiting to be discovered. 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 patient-centered interactions. Simply put, we do what it takes to enable and empower patients and families to focus on health, healing and recovery. You will do this by executing against our three experience pillars, from the patient and family’s perspective: Know Me: Anticipate my needs and status to deliver effective care Show Me the Way: Guide and prompt my actions to arrive at better outcomes and better health Coordinate for Me: Own the complexity of my care through coordination Equal Opportunity Employer Stanford Health Care (SHC) strongly values diversity and is committed to equal opportunity and non-discrimination in all of its policies and practices, including the area of employment. Accordingly, SHC does not discriminate against any person on the basis of race, color, sex, sexual orientation or gender identity and/or expression, religion, age, national or ethnic origin, political beliefs, marital status, medical condition, genetic information, veteran status, or disability, or the perception of any of the above. People of all genders, members of all racial and ethnic groups, people with disabilities, and veterans are encouraged to apply. Qualified applicants with criminal convictions will be considered after an individualized assessment of the conviction and the job requirements. Base Pay Scale: Generally starting at $112.39 - $148.91 per hour The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, specialty and training. This pay scale is not a promise of a particular wage.

Responsibilities

This role involves leading the engineering vision and execution for the chatEHR Generative AI platform, requiring hands-on technical leadership to build scalable infrastructure and engineering discipline. Responsibilities include recruiting, mentoring a high-performing team, defining the technical roadmap, and ensuring all AI applications adhere to strict healthcare regulations and ethical standards.