AI Governance and Evaluation Executive

UT Southwestern Medical Center • Dallas, TX

1d • Onsite

About The Position

The AI Governance and Evaluation Executive is the program and operations leader responsible for implementing, scaling, and continuously improving UT Southwestern’s enterprise approach to responsible AI governance and evaluation. Reporting to the CAIO, the role executes the governance and evaluation roadmap and adoption plan across the health system, research and academic mission, biomedical education, and administrative and business functions. It translates enterprise direction into annual priorities and repeatable workflows for intake, classification, evaluation, review, vendor assessment, deployment conditions, monitoring, reassessment, and stakeholder support. The role maintains enterprise portfolio visibility, drives reuse and consistency, and coordinates cross-functional execution. It works closely with Compliance, Information Security, and Information Technology Services on AI risk management, while those functions retain formal ownership of their respective risk-management domains.

The executive operates the day-to-day Responsible AI Governance and Evaluation program on behalf of the CAIO; manages end-to-end governance and evaluation processes; supports governance of generative and agentic AI; coordinates AI portfolio, vendor, and adoption operations; and partners with domain leaders and risk-owning functions. The role leads governance staff, manages assigned budgets and resources within approved plans, measures program performance, and advises the CAIO on governance operations, evaluation findings, emerging issues, and institutional AI governance maturity.

The position is based in an office setting. Talking is listed as a physical requirement. Salary is commensurate with education, skills, and relevant experience. This is a security-sensitive position subject to criminal history record information checks under Texas Education Code 51.215.

Requirements

• Master’s degree in Public Health, Biomedical Informatics, Data Science, Computer Science, Engineering, Research Administration, or a related field.
• Eight years of progressively responsible experience in AI, digital health, healthcare operations, technology governance, clinical informatics, data analytics, research administration, compliance, or a related field.
• Four years leading people, programs, or complex cross-functional initiatives.
• Demonstrated experience operating cross-functional governance, evaluation, assurance, or enterprise programs.
• Demonstrated experience implementing enterprise roadmaps, operating models, or new capabilities and translating priorities into measurable outcomes.
• Ability to translate enterprise direction into priorities, tradeoffs, repeatable workflows, and measurable program performance.
• Ability to move work across matrixed organizations without relying on command-and-control authority.
• Ability to work comfortably with AI scientists, engineers, clinicians, researchers, and vendors.
• Understanding of when deeper evaluation or stronger controls are warranted.
• Ability to treat governance stakeholders as partners and design timely, usable experiences.
• Ability to evolve governance as models, agents, regulations, and institutional use cases change.
• Strong project and program management and organizational leadership skills.
• Ability to translate complex technical, clinical, regulatory, and ethical issues into practical workflows and decisions.
• Excellent communication, facilitation, negotiation, and stakeholder-management skills.

Nice To Haves

• PhD or additional advanced degree in a related field.
• Experience in an academic medical center, integrated health system, life sciences organization, or similarly complex regulated environment.
• Experience with AI/ML evaluation, deployment, governance, responsible AI, or assurance.
• Experience evaluating AI vendors and coordinating due diligence.
• Technical fluency across LLM ecosystems, MLOps, retrieval and vector technologies, AI APIs and integrations, lifecycle monitoring, and incident-response interfaces sufficient to engage technical teams and assess governance evidence.
• Experience building or scaling a new team or function and managing tools, vendors, contracts, or external resources.
• Familiarity with generative AI, LLMs, multimodal models, foundation models, and agentic AI.
• Working knowledge of healthcare AI evaluation and lifecycle monitoring, including quantitative methods and model cards.
• Familiarity with NIST AI RMF, ISO/IEC 42001, and related responsible AI frameworks or standards.

Responsibilities

• Run the day-to-day enterprise Responsible AI Governance and Evaluation program on behalf of the CAIO.
• Translate program strategy into an annual operating roadmap with priorities, dependencies, resource needs, adoption activities, and measurable outcomes.
• Operationalize AI policies, standards, workflows, decision rights, review pathways, and documentation requirements.
• Coordinate governance across institutional and domain-specific structures, including work with executives and senior leadership.
• Prioritize work based on institutional value, risk, dependencies, and capacity; surface tradeoffs and escalate complex or high-consequence cases.
• Operate intake, triage, AI risk classification, evaluation, multidisciplinary review, decisions, deployment conditions, monitoring, and reassessment workflows.
• Coordinate governance committee agendas, case materials, decisions, action items, and follow-up; maintain authoritative governance records.
• Develop expedited and standardized pathways for low-risk or well-understood AI uses, along with reusable review patterns, templates, evidence packages, evaluation assets, and precedents.
• Provide guidance, consultation, education, and stakeholder support; track service levels, bottlenecks, and outstanding actions and drive closure.
• Implement AI evaluation requirements proportionate to risk, intended use, and deployment context; coordinate assessment of performance, reliability, safety, bias, security considerations, and unintended consequences as applicable.
• Coordinate independent evaluation of consequential AI systems, vendor evidence reviews, prospective validation, simulation, and other assurance activities as appropriate.
• Translate evaluation findings into governance conditions, remediation actions, monitoring requirements, escalation, and measurable outcomes where appropriate.
• Apply governance and evaluation practices to foundation models, LLMs, multimodal models, and agentic AI, including review of access, oversight, autonomous actions, observability, guardrails, testing, and fail-safe mechanisms.
• Convert emerging model and agent capabilities, research, and standards into practical review criteria, test protocols, and playbooks.
• Maintain enterprise visibility of AI systems, vendors, owners, intended uses, risk classifications, evaluation status, and monitoring obligations.
• Coordinate vendor due diligence and evidence collection with Procurement, Legal, Compliance, Information Security, IT, Data, and domain teams, supporting build-buy-partner decisions without assuming procurement or technical architecture ownership.
• Track portfolio priorities, review readiness, dependencies, decisions, and open conditions; prepare concise materials for decision forums.
• Drive adoption through training, guidance, communications, and integration of governance requirements into business, research, clinical, and technology workflows.
• Partner with Compliance and Information Security to identify and assess AI-related risks and incorporate AI considerations into established enterprise risk-management processes.
• Coordinate AI governance requirements, evidence, mitigations, and escalation with risk-owning functions and other control partners; stay current on relevant regulatory requirements, standards, and professional guidance.
• Serve as an operating leadership partner to domain leaders and governance groups, engaging stakeholders early across planning, procurement, research, development, implementation, and operations.
• Lead and oversee UTSW AI Governance Stewards and other governance staff; define roles, structure, decision rights, and ways of working, and develop staff expertise and partnerships.
• Manage assigned budgets, governance and evaluation tooling, contracts, and external resources within approved plans.
• Maintain a balanced program scorecard and use data to improve throughput, consistency, adoption, and institutional confidence.
• Advise the CAIO, represent the Office of the CAIO in designated forums, facilitate organizational decisions, resolve operational barriers, escalate significant concerns, and prepare executive-level reporting.
• Explain complex AI, governance, and evaluation concepts clearly to technical and nontechnical audiences.

Benefits

• PPO medical plan, available day one at no cost for full-time employee-only coverage.
• 100% coverage for preventive healthcare with no copay.
• Paid Time Off, available day one.
• Retirement Programs through the Teacher Retirement System of Texas (TRS).
• Paid Parental Leave Benefit.
• Wellness programs.
• Tuition Reimbursement.
• Public Service Loan Forgiveness (PSLF) Qualified Employer.
• Competitive and comprehensive benefits package for eligible employees, including healthcare, PTO, paid holidays, on-site childcare, and merit increases.

What This Job Offers

• Job Type: Full-time
• Career Level: Executive