VP, Artificial Intelligence Vendor Governance & Oversight (Remote)

Molina Healthcare•Long Beach, CA

2d•Remote

About The Position

The VP, Artificial Intelligence Vendor Governance & Oversight leads the executive strategy, vision, and direction for Molina’s enterprise AI governance and vendor oversight strategy and operating framework. The role is responsible for AI vendor oversight, regulatory compliance, risk management, model governance, and value protection across the AI lifecycle. In partnership with technology and business leaders, the VP establishes decision rights, controls, and monitoring practices that enable responsible, secure, and consistent scaling of vended AI solutions across the organization. The role develops enterprise policies, standards, governance processes, and oversight mechanisms for AI tools, models, processes, and technology enhancements. It leads risk-based review and approval of AI use cases and third-party solutions throughout their lifecycle, establishes enterprise inventories and monitoring, and defines escalation and remediation practices. The VP also leads governance committees, partners with cross-functional stakeholders to integrate AI oversight with existing enterprise risk frameworks, ensures regulatory and contractual compliance, and provides executive reporting on portfolio risk and responsible AI adoption. The position includes building and developing AI governance capabilities and representing Molina in external forums.

Requirements

At least 12 years of progressive experience in managed care, governance, compliance, enterprise risk management, technology risk, privacy, information security, audit, healthcare operations, or an equivalent combination of relevant education and experience.
At least 7 years of management or leadership experience.
Demonstrated experience establishing or leading governance frameworks for artificial intelligence, emerging technology, data, models, or other high-impact enterprise capabilities in regulated environments.
Strong knowledge of healthcare regulatory and compliance requirements, enterprise risk management, model risk, data privacy, cybersecurity, and third-party risk management.
Experience designing policies, standards, controls, risk assessments, approval processes, monitoring mechanisms, and executive reporting for complex enterprise programs.
Conceptual understanding of AI and machine learning technologies and the solution lifecycle, from ideation and development through deployment, monitoring, and retirement.
Strong understanding of responsible AI principles, including fairness, transparency, explainability, accountability, human oversight, privacy, security, and reliability.
Demonstrated ability to translate evolving regulatory requirements and technical risks into practical business controls and operating practices.
Strong executive communication, cross-functional collaboration, stakeholder management, and influence skills in a matrixed environment.
Demonstrated ability to lead, mentor, and develop high-performing teams and drive initiatives from concept through implementation and sustained operation.
Experience assessing third-party AI products, cloud-based AI services, large language models, generative AI, agentic AI, machine learning, or automated decision-support systems.
Experience operating with ambiguity and balancing innovation, member and patient impact, regulatory obligations, operational feasibility, and business value.

Nice To Haves

Master’s degree in business administration, Healthcare Administration, Information Technology, Data Science, Law, Public Policy, Risk Management, or a related field.
Experience in health insurance, managed care, Medicare, Medicaid, Marketplace, clinical operations, or other highly regulated healthcare environments.
Experience with AI governance frameworks, model risk management standards, privacy impact assessments, security risk assessments, regulatory readiness, or audit support.
Relevant certification in risk, privacy, security, compliance, audit, governance, or artificial intelligence.

Responsibilities

Lead Molina’s enterprise AI vendor governance strategy and operating framework, including governance bodies, decision rights, approval pathways, policies, standards, controls, and guardrails.
Develop and maintain enterprise policies and standards for responsible AI, model risk management, data privacy, cybersecurity, regulatory compliance, explainability, human oversight, documentation, and monitoring.
Lead risk-based intake, review, and approval processes for AI use cases and vended solutions throughout the AI lifecycle, from ideation and development through deployment, operation, material change, and retirement.
Establish and maintain the enterprise AI inventory, risk classification methodology, control library, evidence requirements, and performance-monitoring mechanisms.
Define escalation protocols and accountability for AI risks, control gaps, incidents, exceptions, and remediation, including recommendations to pause, restrict, modify, or retire solutions when risk thresholds are exceeded.
Chair or provide executive leadership to AI governance and approval committees, ensuring timely, transparent, documented decisions aligned with enterprise priorities and risk appetite.
Partner with Legal, Compliance, Privacy, Information Security, Internal Audit, Enterprise Risk Management, Technology, Clinical, Operations, and business leaders to integrate AI governance into enterprise risk and control frameworks.
Ensure vended AI solutions comply with applicable CMS, state, healthcare, privacy, security, and contractual requirements, with attention to PHI, PII, clinical and coverage decision support, member communications, and other high-impact managed care use cases.
Lead third-party AI product and service oversight, including vendor due diligence, contracting requirements, risk assessments, control validation, performance monitoring, and exit or contingency planning.
Establish executive reporting and metrics covering AI portfolio risk, control effectiveness, regulatory readiness, incidents, remediation, and responsible AI adoption.
Collaborate with AI Institutional, Retail, Middleware, Engineering, and business value-stream leaders to embed governance in solution design, implementation planning, change management, vended solutions, and value realization.
Represent Molina in external AI governance, regulatory, industry, and vendor forums; monitor emerging laws, standards, and practices and translate changes into enterprise requirements.
Build and develop high-performing AI governance and oversight capabilities through team leadership, role clarity, governance education, and enterprise-wide awareness of responsible AI expectations.