Director, AI & Automation

As a community, the University of Rochester is defined by a deep commitment to Meliora - Ever Better. Embedded in that ideal are the values we share: equity, leadership, integrity, openness, respect, and accountability. Together, we will set the highest standards for how we treat each other to ensure our community is welcoming to all and is a place where all can thrive.

Job Location (Full Address): 30 Corporate Woods, Brighton, New York, United States of America, 14623

Opening Worker Subtype:

Regular

Time Type Full time

Scheduled Weekly Hours 40

Department 900300 Office of Digital Strategy and Innovation

Work Shift UR - Day (United States of America)

Range UR URG 118

Compensation Range $141,000.00 - $211,600.00

The referenced pay range represents the minimum and maximum compensation for this job. Individual annual salaries/hourly rates will be set within the job’s compensation range, and will be determined by considering factors including, but not limited to, market data, education, experience, qualifications, expertise of the individual, and internal equity considerations. Responsibilities Leads the operational execution, portfolio oversight, governance, continued advancement, and data integration strategy for AI (Artificial Intelligence) & Automation across University of Rochester Medicine. Establishes and owns the tactical and operational plans necessary to translate strategy into measurable execution across AI portfolio governance, technical architecture, data integration, vendor coordination, and stakeholder engagement. Manages and develops staff; serves as a primary technical and operational representative for AI initiatives; translates the organizational AI strategy into University of Rochester Medicine capabilities; and influences cross-functional partners across clinical, operational, ISD, data governance, security, and vendor domains. Ensures the prioritization of the AI portfolio, its architecture, and technology selection.

Essential Functions

• Establishes enterprise governance processes for prioritization, intake, oversight, and lifecycle management of the AI portfolio. Researches and analyzes data to recommend investment priorities, continuation, acceleration, or retirement of initiatives based on strategic value, organizational readiness, risk, and return on investment to leader. Meets with teams across the University of Rochester Medicine enterprise to understand and inventory use of current AI tools. Based on these findings, develops and maintains a comprehensive, current inventory of AI tools, initiatives, and vendor relationships across the University of Rochester Medicine, ensuring the AI & Automation pillar has complete visibility into the Medical Center’s AI landscape. Identifies conflicts, redundancies, and gaps across the AI portfolio, surfacing findings to leader with recommendations for portfolio adjustments, resource reallocation, or initiative discontinuation. Tracks adoption, usage, and performance data for AI initiatives across the portfolio, synthesizing trends into actionable intelligence for pillar leadership and governance bodies. Develops and executes a standardized assessment process to evaluate the ongoing performance, accuracy, and maintenance status of AI initiatives and community-built assistants, flagging concerns to leader for follow-up. Produces portfolio reporting for oversight and governance committees, translating portfolio data into governance-ready formats. Coordinates with the Project Manager and Business Analysts to ensure portfolio tracking systems are maintained and reporting cadences are met. Presents portfolio recommendations to executive governance committees and influences enterprise investment decisions.
• Leads the identification, acquisition, and integration of data required to enable AI initiatives across University of Rochester Medicine, ensuring projects have appropriate access to clinical, operational, research, and administrative data sources. Partners with clinical, operational, analytics, and information technology (IT) teams to identify data dependencies, data ownership, stewardship requirements, and data quality considerations for proposed AI initiatives. Serves as the primary liaison with IT for data-related requests, including access provisioning, data onboarding, integration prioritization, and coordination of enterprise data resources. …