U

University of Rochester

Private research university in Rochester, NY

Director – AI and Automation

IT OperationsConfirmed live in the last 24 hours
Full-timeBrighton, NY, USA$141k - $211.6k /yrIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Data Science, Information Systems, Biomedical Informatics, or a related field, plus 8 years of progressive experience in technical architecture, systems integration, technology portfolio management, or a related field, including 3 years of experience in a health system or healthcare IT environment.
  • AI or digital health experience is required.
  • Experience leading or managing a team, including setting priorities, providing guidance, and supporting staff development, is required.
  • Knowledge of healthcare privacy, security, and compliance requirements, including HIPAA and data governance, is required.
  • Ability to assess the technical feasibility of AI integrations and identify dependencies, risks, and blockers before resources are committed is required.
  • Experience developing and maintaining a portfolio of technology initiatives, including tracking performance metrics and reporting to governance bodies, is required.
  • Working knowledge of AI and machine-learning concepts, architectures, and integration patterns, including large language models, retrieval-augmented generation-based systems, and agentic frameworks, is required.
  • Experience presenting to senior leadership or governance bodies on portfolio performance and strategic recommendations is required.

Responsibilities

  • Lead the operational execution, portfolio oversight, governance, continued advancement, and data integration strategy for AI and Automation across University of Rochester Medicine.
  • Establish and own tactical and operational plans to translate strategy into measurable execution across AI portfolio governance, technical architecture, data integration, vendor coordination, and stakeholder engagement.
  • Ensure prioritization of the AI portfolio, its architecture, and technology selection.
  • Establish enterprise governance processes for prioritization, intake, oversight, and lifecycle management of the AI portfolio.
  • Research and analyze data to recommend investment priorities, continuation, acceleration, or retirement of initiatives based on strategic value, organizational readiness, risk, and return on investment.
  • Meet with teams across University of Rochester Medicine to understand and inventory current AI tool use; develop and maintain a comprehensive inventory of AI tools, initiatives, and vendor relationships.
  • Identify conflicts, redundancies, and gaps across the AI portfolio, and recommend portfolio adjustments, resource reallocation, or initiative discontinuation to leadership.
  • Track adoption, usage, and performance data for AI initiatives and synthesize trends into actionable intelligence for leadership and governance bodies.
  • Develop and execute a standardized assessment process to evaluate the ongoing performance, accuracy, and maintenance status of AI initiatives and community-built assistants, and flag concerns for follow-up.
  • Produce portfolio reporting for oversight and governance committees, translating portfolio data into governance-ready formats.
  • Coordinate with the Project Manager and Business Analysts to maintain portfolio tracking systems and meet reporting cadences.
  • Present portfolio recommendations to executive governance committees and influence enterprise investment decisions.
  • Lead the identification, acquisition, and integration of data required for AI initiatives, ensuring appropriate access to clinical, operational, research, and administrative data sources.
  • Partner with clinical, operational, analytics, and information technology teams to identify data dependencies, ownership, stewardship requirements, and quality considerations for proposed AI initiatives.
  • Serve as the primary liaison with information technology for data-related requests, including access provisioning, data onboarding, integration prioritization, and coordination of enterprise data resources.
  • Work 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.
  • Coordinate development and execution of data acquisition plans, ensuring required datasets are available, fit for purpose, and delivered within project timelines.
  • Evaluate data readiness by assessing availability, quality, completeness, consistency, and sustainability, and identify risks and remediation plans before resources are committed.
  • Maintain visibility into enterprise data integration efforts supporting AI initiatives and facilitate resolution of data-related barriers with information technology, analytics teams, vendors, and operational stakeholders.
  • Oversee compliance with University data use agreements, governance requirements, and approved data-sharing practices; develop initial drafts of data use agreements and coordinate reviews and approvals.
  • Establish enterprise standards for AI data readiness and governance, and repeatable processes for onboarding new data sources in alignment with enterprise data management practices.
  • Direct and support cross-functional decisions regarding enterprise data access, stewardship, interoperability, and long-term sustainability.
  • Serve as the primary technical point of contact for initiatives across vendors, ISD, and internal build partners.
  • Evaluate vendor technical claims for accuracy before commitments are made by testing assertions against known constraints of the University of Rochester Medicine environment.
  • Manage ongoing technical relationships with AI vendors, conduct technical check-ins, track delivery against contracted scope, identify gaps between planned and delivered functionality, document discrepancies, drive resolution through technical leads, and escalate risks to leadership.
  • Design and evaluate integration architecture for AI initiatives across University of Rochester Medicine, including how solutions connect to Epic, enterprise data platforms, and other clinical and operational systems.
  • Translate technical constraints, risks, and architecture decisions into plain-language implications for clinical and operational stakeholders, and convert business and clinical needs into technical requirements for information technology and vendors.
  • Present technical trade-offs in governance meetings and cross-functional project discussions to support informed stakeholder commitments.
  • Establish and maintain working relationships with clinical, operational, and vendor partners through regular engagement as a technical point of contact.
  • Influence enterprise technology decisions and negotiate technical direction to align with institutional priorities.
  • Provide day-to-day guidance to assigned staff through regular check-ins, work review, and coaching, maintaining alignment with pillar priorities and standards.
  • Represent AI and Automation in senior stakeholder conversations, governance meetings, and cross-functional discussions in the absence of or alongside leadership.
  • Monitor initiative progress through regular check-ins with assigned staff, identify risks or delays, and escalate as needed.
  • Contribute portfolio intelligence and technical expertise to strategy development and leadership decision-making.
  • Provide supervision and coaching to ensure staff work efficiently and collaboratively as a cohesive team.
  • Manage staff human-resources needs, including making and approving hiring decisions, supporting onboarding and continued training, providing ongoing supervision, managing personnel issues and actions, and conducting performance reviews.
  • Build and mature organizational AI capabilities through workforce planning, succession planning, mentoring, and organizational design.
  • Lead managers and cross-functional teams through organizational change and AI adoption.
  • Monitor emerging AI architectures, tools, and platforms relevant to healthcare delivery, including agentic frameworks, retrieval-augmented generation patterns, and model infrastructure.
  • Evaluate new technical approaches for applicability to University of Rochester Medicine and present findings and recommendations for pilot consideration, adoption, or deferral.
  • Assess vendor and open-source tooling trends to anticipate capabilities expected to become available in the next 12–18 months.
  • Brief leadership on technical and market developments that could affect portfolio strategy, prioritization, or vendor selection.
  • Benchmark University of Rochester Medicine’s AI capabilities against peer academic medical centers through literature review, conference engagement, and peer networks, identifying capability gaps or emerging risks.
  • Support leadership in developing and presenting multi-year recommendations for enterprise AI capabilities and roadmap evolution.
  • Perform other duties as assigned.

Desired Qualifications

  • A master's degree and 2 years of experience in a leadership or senior individual-contributor role with team-guidance responsibilities.
  • Experience in an academic medical center or large health-system environment.
  • Experience with Epic, including integration patterns and application programming interfaces.
  • Knowledge of healthcare data standards and interoperability frameworks, including Health Level Seven and Fast Healthcare Interoperability Resources.
  • Experience working within enterprise architecture functions and collaborating with data architects, solutions architects, and infrastructure teams.
  • Experience with data access governance, including data use agreements, access provisioning, and approval workflows.
  • Ability to evaluate vendor technical claims and manage scope and delivery against technical commitments.
  • Experience with enterprise data platforms such as Databricks, Denodo, or Snowflake, or equivalent platforms.
  • Experience designing or implementing data pipelines and integration architectures in complex enterprise environments.
  • Experience integrating AI tools with non-Epic clinical and operational systems.
  • Fluency with Azure AI tools, including Azure OpenAI Service and Azure API Management.
  • Experience with on-premises model hosting and hybrid cloud/on-premises AI deployment patterns.
  • Familiarity with large language model deployment patterns, including model serving, prompt engineering, and evaluation frameworks.
  • Epic Bridges certification.
  • Epic Clarity, Caboodle, and/or Chronicles certification.
  • Azure AI Engineer Associate or Solutions Architect certification.

About the Company

University of Rochester

Private research university in Rochester, NY

The University of Rochester is a research university with programs spanning the humanities, health care, business, education, music, engineering, and the sciences.

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