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. Works with data governance, privacy, compliance, and information security teams to ensure AI initiatives meet institutional requirements for data access, use, retention, and protection before deployment. Coordinates the development and execution of data acquisition plans for AI initiatives, ensuring required data sets are available, fit for purpose, and delivered within project timelines. Evaluates data readiness for proposed AI initiatives by assessing data availability, quality, completeness, consistency, and sustainability, identifying risks and remediation plans before resources are committed. Maintains visibility into enterprise data integration efforts supporting AI initiatives and facilitates resolution of data-related barriers through collaboration with IT, analytics teams, vendors, and operational stakeholders. Oversees compliance with University data use agreements, governance requirements, and approved data-sharing practices for AI initiatives. Develops initial drafts of data use agreements and coordinates required reviews and approvals. Establishes enterprise standards for AI data readiness and governance. Establishes and maintains repeatable processes for onboarding new data sources into AI initiatives, promoting consistency, scalability, and alignment with enterprise data management practices. Directs and supports cross-functional decisions regarding enterprise data access, stewardship, interoperability, and long-term sustainability.
• Serves as the primary technical point of contact for initiatives across vendors, ISD, and internal build partners. Evaluates vendor technical claims for accuracy before commitments are made, testing assertions against known constraints of the University of Rochester Medicine environment. Manages ongoing technical relationships with AI vendors, running technical check-ins, tracking delivery against contracted scope, and identifying gaps between planned and delivered functionality across vendor and internally built AI initiatives, documents discrepancies, and drives resolution through the appropriate technical leads, escalating to leadership when commitments are at risk. Designs and evaluates integration architecture for AI initiatives across UR Medicine, defining how proposed solutions connect to Epic, enterprise data platforms, and other clinical and operational systems. Translates technical constraints, risks, and architecture decisions into plain-language implications for clinical and operational stakeholders, and converts business and clinical needs into concrete technical requirements for ISD and vendors. Presents technical trade-offs clearly in governance meetings and cross-functional project discussions, providing stakeholders with the information they need to make informed commitments. Establishes and maintains working relationships with clinical, operational, and vendor partners through regular engagement, serving as a consistent and credible technical point of contact. Influences enterprise technology decisions and negotiates technical direction to ensure alignment with institutional priorities.
• Provides day-to-day guidance to assigned staff through regular check-ins, work review, and coaching, maintaining alignment with pillar priorities and standards. Represents the AI & Automation in senior stakeholder conversations, governance meetings, and cross-functional discussions in the absence of or alongside leadership. Monitors initiative progress through regular check-ins with the assigned staff, identifying risks or delays and escalating to leadership as needed. Contributes to strategy development, bringing portfolio intelligence and technical expertise to inform leader decision-making. Provides supervision and coaching to ensure staff work efficiently and collaboratively as a cohesive, effective team. Manages human resources needs of staff, including, but not limited to: making and approving hiring decisions, supporting onboarding and continued training, providing ongoing supervision, managing personnel issues and actions, and conducting performance reviews. Builds and matures organizational AI capabilities through workforce planning, succession planning, mentoring, and organizational design. Leads managers and cross-functional teams through organizational change and AI adoption.
• Monitors emerging AI architectures, tools, and platforms relevant to healthcare delivery, including agentic frameworks, RAG patterns, and model infrastructure. Evaluates new technical approaches for applicability to University of Rochester Medicine's environment and presents findings to leader with recommendations for pilot consideration, adoption, or deferral. Assesses vendor and open-source tooling trends to anticipate capabilities that will become available or expected in the next 12-18 months. Briefs leader on relevant technical and market developments that could affect portfolio strategy, prioritization, or vendor selection. Benchmarks University of Rochester Medicine's AI capabilities against peer academic medical centers through literature review, conference engagement, and peer network relationships, identifying gaps or emerging risk of falling behind. Provides support to leadership in the development and presentation of multi-year recommendations for enterprise AI capabilities and roadmap evolution.
• Other duties as assigned.

Minimum Education & Experience:

• Bachelor's degree in Computer Science, Data Science, Information Systems, Biomedical Informatics, or related field and 8 years of progressive experience in technical architecture, systems integration, technology portfolio management, or a related field including 3 years' experience in a health system or healthcare IT environment required.
• AI or digital health experience required.
• Master's degree and 2 years' experience in a leadership or senior individual contributor role with team guidance responsibilities preferred
• Or equivalent combination of education and experience.

Knowledge, Skills & Abilities:

• Experience leading or managing a team, including setting priorities, providing guidance, and supporting staff development required.
• Knowledge of healthcare privacy, security, and compliance requirements including HIPAA and data governance required.
• Ability to assess technical feasibility of AI integrations, identifying dependencies, risks, and blockers before resources are committed required.
• Experience developing and maintaining a portfolio of technology initiatives, including tracking performance metrics and reporting to governance bodies required.
• Working knowledge of AI/ML concepts, architectures, and integration patterns including LLMs, RAG-based systems, and agentic frameworks required.
• Experience presenting to senior leadership or governance bodies on portfolio performance and strategic recommendations required.
• Experience in an academic medical center or large health system environment preferred.
• Experience with Epic including integration patterns and APIs preferred.
• Knowledge of healthcare data standards and interoperability frameworks including HL7 and FHIR preferred.
• Experience working within enterprise architecture functions, collaborating with data architects, solutions architects, and infrastructure teams preferred.
• Experience with data access governance including data use agreements, access provisioning, and approval workflows preferred.
• Ability to evaluate vendor technical claims and manage scope and delivery against technical commitments preferred.
• Experience with enterprise data platforms including Databricks, Denodo, Snowflake, or equivalent preferred.
• Experience designing or implementing data pipelines and integration architectures in complex enterprise environments preferred.
• Experience integrating AI tools with non-Epic clinical and operational systems preferred.
• Fluency with Azure AI tools including Azure OpenAI Service and Azure API Management preferred.
• Experience with on-premises model hosting and hybrid cloud/on-prem AI deployment patterns preferred.
• Familiarity with LLM deployment patterns including model serving, prompt engineering, and evaluation frameworks preferred.

Licenses and Certifications:

• Epic Bridges certification preferred.
• Epic Clarity, Caboodle and/or Chronicles certification preferred.
• Azure AI Engineer Associate or Solutions Architect preferred.

The University of Rochester is committed to fostering, cultivating, and preserving an inclusive and welcoming culture to advance the University's Mission to Learn, Discover, Heal, Create - and Make the World Ever Better. In support of our values and those of our society, the University is committed to not discriminating on the basis of age, color, disability, ethnicity, gender identity or expression, genetic information, marital status, military/veteran status, national origin, race, religion, creed, sex, sexual orientation, citizenship status, or any other characteristic protected by federal, state, or local law (Protected Characteristics). This commitment extends to non-discrimination in the administration of our policies, admissions, employment, access, and recruitment of candidates, for all persons consistent with our values and based on applicable law.