
Real job — pulled straight from UC San Francisco’s careers page · Verified October 16, 2026 · No reposts.
Job description
UC San Francisco is hiring a Research AI & Data Enablement Specialist — a full-time, based in San Francisco, CA role. Apply directly on UC San Francisco's careers page below.
Research AI & Data Enablement Specialist
Location: San Francisco, CA, United States
Certain terms and conditions of employment for this position, including the rate of pay, benefits, etc., are currently subject to negotiation with the appropriate union.
Applies professional concepts and UCSF policies and procedures to increase successful researcher adoption of research data assets, computational environments, AI capabilities, and research technologies. Independently analyzes researcher needs and adoption barriers; identifies opportunities to apply AI and automation to streamline research processes, reduce manual effort, and improve researcher productivity; develops, tests, and operationalizes AI-enabled and automated workflow solutions within supported research environments; develops and maintains scalable onboarding, documentation, knowledge resources, workflow examples, and AI-assisted support capabilities. Validates researcher-facing workflows and recommends improvements to research services and user experience. Works across researchers, product management, data engineering, research infrastructure, and support teams to translate complex technical capabilities into practical guidance. Within defined procedures and practices, determines appropriate action and escalates product strategy, infrastructure priorities, architectural direction, service portfolio, funding priorities, and institutional communications decisions to responsible leadership.
Department Overview
UCSF Academic Research Services supports researchers in discovering, understanding, and effectively using institutional research data assets, computational environments, AI capabilities, and related research technologies. The ARS Research Data Services and Information Commons program works across research, product, data engineering, infrastructure, and support teams to improve researcher experience, increase successful self-service adoption, and develop scalable services and reusable institutional knowledge.
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