Sutter Health AI Physician Fellowship Opportunity (Any Sutter Health Location)

Sutter Health - Bay Area

10d

About The Position

This internal fellowship opportunity is open to physicians within Sutter Health residency programs and associated medical groups who are interested in contributing to the advancement of AI in healthcare education and clinical practice. The role is structured as a 0.5 FTE fellowship appointment combined with a 0.5 FTE clinical practice component, ensuring continued patient care responsibilities within the Sutter footprint. Clinical placement will be coordinated based on the selected candidate's medical group, specialty, and geographic location to support seamless integration of both responsibilities. Fellows serve as leaders in advancing AI literacy, curriculum innovation, and educational transformation. They work alongside trainees, faculty, and health system leaders to design, implement, and evaluate AI-enabled educational strategies that enhance clinical reasoning, assessment, feedback, and patient care training. Through hands-on engagement with real-world AI tools and educational technologies, fellows help shape how future physicians learn to safely and effectively use AI in clinical environments. Embedded within Academic Affairs and the Center for Applied AI, fellows gain direct exposure to the development, validation, and governance of AI solutions and medical education faculty. This vantage point enables them to translate emerging technologies into meaningful educational applications, ensuring alignment with clinical standards, ethical principles, and accreditation requirements. By the end of the program, fellows graduate as AI-competent clinician-educators prepared to lead curricular reform, guide responsible AI adoption, and shape the future of medical education.

Requirements

MD or DO degree from an accredited medical school. Completion of an ACGME-accredited residency program by the start date.
Board-eligible or board-certified in relevant specialty; eligible for state medical licensure. Additional certifications (e.g., ACLS, BLS) as required by clinical duties.
Curiosity and enthusiasm for AI and its potential to improve care delivery.
Strong communication skills and the ability to translate complex technical ideas into practical clinical language.
Comfort working with multidisciplinary teams (clinicians, IT, data science, operations, education).
Organizational skills and the ability to manage multiple concurrent projects.
Commitment to patient-centered, equitable, and ethically responsible use of AI.
Knowledge of patient care delivery guidelines/policy as evidenced by care delivery.
Demonstrated awareness of safe clinical practice within own limitations and the environment in which they are practicing.
General knowledge of computer applications, such as Microsoft Office Suite (Word, Excel and Outlook), electronic health records (EHR), and EPIC.

Nice To Haves

Experience in data science, software development, technology consulting or informatics preferred.

Responsibilities

Gather frontline feedback about AI tools and workflows; surface needs, concerns, and opportunities to program leadership.
Help operationalize AI-related priorities set by system leadership within day-to-day clinical environments.
Participate in identifying and prioritizing AI use cases in collaboration with clinical, IT, data science, and operations partners.
Contribute to workflow design, pilot planning, and implementation of AI and decision-support tools.
Help define and monitor key metrics (quality, efficiency, equity, experience) related to AI initiatives.
Collaborate in the design and refinement of educational curricula for UME and GME that thoughtfully integrate AI, digital health, and systems-based practice concepts.
Develop and deliver teaching sessions on clinical AI fundamentals for residents, fellows, faculty, and staff.
Support residents and students interested in AI-related QI, research, or scholarly projects.
Assist in evaluating AI tools for safety, bias, and alignment with organizational values and regulatory expectations.
Participate in AI governance, risk assessment, and post-implementation reviews as appropriate.
Promote responsible and equitable use of AI, with attention to underserved populations and disparities.
Engage in scholarly projects (e.g., QI studies, implementation science, educational scholarship) related to AI in practice.
Contribute to abstracts, presentations, or manuscripts describing AI-related innovations and outcomes.

Benefits

Join a dynamic and physician-led organization committed to clinical excellence, collaboration, and career growth.
Enjoy a competitive compensation and benefits package, a supportive team environment, and a strong commitment to work-life balance and professional development!

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