Associate Director, Institutional AI Governance

As the Associate Director, Institutional AI Governance in our Data Impact & Governance department, you will lead the governance processes that safeguard patient trust, ensure responsible AI innovation, and prepare the institution for the rapidly evolving regulatory landscape. This is a high-impact leadership role where your expertise will influence enterprise-wide decisions across clinical care, research, education, and operations.

We offer a unique opportunity to build and operationalize one of the most advanced AI governance models in healthcare-working at the intersection of ethics, technology, policy, risk management, and institutional strategy.

What's in it for you?

• Exceptional Benefits Package: MD Anderson provides paid medical benefits , generous PTO , and highly competitive retirement plans , supporting your health, stability, and long-term financial planning.
• Strategic Leadership Impact: Directly shape institutional standards, governance models, and decision frameworks that guide safe, ethical, and scalable AI deployment.
• Career Advancement & Visibility: Collaborate with executive leadership, institution-wide governance councils, and multidisciplinary experts across AI, clinical care, research, and compliance.
• Mission-Driven Work: Your leadership ensures AI enhances patient outcomes, strengthens research integrity, and supports MD Anderson's mission to end cancer.
• Growth & Innovation: Work in a forward-thinking environment that invests in emerging technology, responsible AI, and continuous institutional improvement.

Summary

The Associate Director, Institutional AI Governance is responsible for defining, operating, and continuously improving the institution's AI governance framework. This role ensures governance decisions are executed effectively, risks are identified early, AI lifecycle processes are followed consistently, and the institution remains compliant and audit-ready as AI adoption grows. The role orchestrates cross-functional participation, manages governance workflows and documentation, and ensures that oversight policies translate into repeatable and scalable operational processes.

Success requires expertise in AI governance, regulatory interpretation, risk assessment, communication strategy, and institutional alignment across complex academic medical center environments.

Major Work Activities

1. AI Governance Framework & Operating Model

• Lead and evolve the institutional AI governance framework, including policies, standards, and operating procedures.
• Define and maintain governance checkpoints across the AI lifecycle (intake, review, approval, monitoring, retirement).
• Design and operate the AI governance operating model, including workflows, documentation standards, and decision processes.
• Coordinate cross-functional engagement to ensure governance execution without duplicating operational ownership.
• Provide oversight for governance tooling, AI inventory management, and reporting standards.
• Monitor emerging AI regulations, ethics guidance, and best practices; translate insights into governance actions.
• Continuously improve governance effectiveness, efficiency, stakeholder experience, and scalability.

2. Execution & Orchestration of Institutional AI Governance

• Operate the centralized AI governance process supporting the Institutional AI Governance Council and related committees.
• Oversee governance intake, triage, and review activities across clinical, research, operational, and enterprise AI initiatives.
• Ensure governance reviews include appropriate evidence on use cases, risks, controls, performance, impact, and value.
• Maintain an authoritative institution-wide AI inventory with complete lifecycle traceability.
• Document, communicate, and track governance decisions, required controls, and approval conditions.
• Produce governance reporting on AI risks, safety, performance, and institutional impact for executive oversight.
• Serve as the escalation point for governance process issues, exceptions, and questions.

3. Stakeholder Engagement & Institutional Alignment

• Facilitate collaboration among clinical, research, technical, legal, compliance, privacy, and security stakeholders.
• Provide clear guidance on governance requirements, expected evidence, and lifecycle obligations.
• Communicate AI governance requirements and decisions in a timely, clear, and actionable manner.
• Support governance bodies by framing tradeoffs, risks, and decision paths in complex and time-sensitive contexts.

Competencies

Technical Expertise

• Applied understanding of AI/ML systems in healthcare to evaluate risks, controls, and intended use.
• Experience implementing and operating AI governance platforms and automated workflows.
• Strong knowledge of regulatory, legal, and ethical requirements for AI in healthcare.
• Ability to define governance expectations for AI monitoring, re-review, change management, and retirement.

Analytical Expertise

• Translate regulatory or policy requirements into enforceable standards and review criteria.
• Assess AI systems against governance requirements and recommend defensible decisions.
• Identify, prioritize, and communicate AI risk across clinical, operational, and regulatory domains.
• Evaluate AI impact and safety using measurable indicators.
• Convert governance decisions into actionable control requirements and conditions.

Oral & Written Communication

• Create standardized governance communication templates, intake guidance, and reporting formats.
• Communicate decisions, rationale, and control requirements clearly to a variety of audiences.
• Prepare audit-ready governance documentation and exception justifications.
• Facilitate difficult governance discussions and communicate decisions under time pressure and regulatory scrutiny.

Education Required: Bachelor's degree.

Preferred Education: Bachelor's degree in Business Administration, Healthcare Administration, Law, Computer Science, Data Science, or a related discipline. Master's Degree (MBA, MHA, or similar) or advanced degree in a related field such as Computer Science, Data Science, Biomedical Informatics, Public Policy, or Law.

Experience Required:

Eight years of experience with data governance, data analytics, information services, or data management, to include five years of supervisory or management experience. May substitute required education degree with additional years of equivalent experience on a one-to-one basis.

Preferred Experience:

• Experience governing AI, analytics, or model-based systems in clinical, research, or other high-risk operational environments
• Familiarity with healthcare AI governance frameworks, regulations, and standards (e.g., NIST, ISO, FDA, HIPAA, HHS, ONC, ACR, or equivalents)
• Experience scaling AI governance processes across expanding AI portfolios while balancing rigor, efficiency, and adoption
• Experience defining, measuring, and tracking AI impact, value, safety, and performance across the AI lifecycle

The University of Texas MD Anderson Cancer Center offers excellent benefits , including medical, dental, paid time off , retirement , tuition benefits, educational opportunities, and individual and team recognition.

This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.

It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law.

Additional Information

• Requisition ID: 178273
• Employment Status: Full-Time
• Employee Status: Regular
• Work Week: Days
• Minimum Salary: US Dollar (USD) 146,500
• Midpoint Salary: US Dollar (USD) 183,000
• Maximum Salary : US Dollar (USD) 219,500
• FLSA: exempt and not eligible for overtime pay
• Fund Type: Hard
• Work Location: Remote (within Texas only)
• Pivotal Position: Yes
• Referral Bonus Available?: Yes
• Relocation Assistance Available?: Yes

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