RAIB Governance Lead Director

McKesson is an impact-driven Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights products and services that make quality care more accessible and affordable. Here we focus on the health happiness and well-being of you and those we serve we care.

What you do at McKesson matters. We foster a culture where you can grow make an impact and are empowered to bring new ideas. Together we thrive as we shape the future of health for patients our communities and our people. If you want to be part of tomorrows health today we want to hear from you.

Role Summary:

The AI Governance Operations Lead ensures that McKessons Responsible AI framework is executed consistently across the enterprise. This role operationalizes the governance structures defined by the Enterprise AI Council (EAIC) and the Responsible AI Boards (RAIBs) overseeing intake triage risk assessment workflows quality assurance documentation and monitoring aligned with enterprise AI governance standards. The position ensures compliant transparent and risk aligned AI adoption across business units.

Key Responsibilities:

• Manage the Enterprise Intake Process: maintain central intake form and routing process to ensure process reliability
• Maintain update and implement enterprise AI Governance standards taxonomies definitions and risk-classification logic as the EAIC continues to develop them.
• Ensure alignment between AI governance standards and broader enterprise policies
• Support Appropriate Routing Intake & Quality of Submissions by validating intake submissions for completeness and ensure proper routing.
• Manage enterprise-level exception requests and coordinate routing for EAIC level escalation
• Implement EAIC directed process updates; ensure required adjustments to intake logic workflow dashboards etc. as directed by the EAIC
• Ensuring Operational Reliability: identify diagnose and resolve technical failures to support consistent governance processes
• Conduct trend analysis on AI use case submissions risk tiers model types vendor maturity and recurring issues
• Identify systemic risks gaps or repeated exceptions across RAIBs and escalate them to the EAIC
• Maintain repository of approved/flagged AI vendors and relevant risk data
• Support EAIC monitoring function by creating enterprise reports risk trend summaries and thematic insights.
• Maintain dashboards and workflow visibility for RAIB and EAIC leadership including status updates approval milestones and escalations requested by your applicable RAIB
• Provide enterprise insights develop and deliver dashboards and materials that provide enterprise level insights to support EAIC EOT and RAIB monitoring and decision making.
• Coordinate with RAIB leaders other RAIB Operations Leads and subject matter experts to ensure coordination and communication across AI Governance landscape.
• Develop and maintain training materials playbooks and guidance for business submitters and RAIB participants as needed.
• Deliver or coordinate training or office hours to business teams to ensure intake quality and adoption of governance processes
• Create and update role-based training for RAIB members SMEs and PMOs
• Actively participate in the RAIB Operations/Lead community of practice to align processes develop best practices and trouble-shoot new and emerging challenges to the AI governance process
• Partner with Legal Compliance Cybersecurity Procurement and other stakeholder teams to socialize governance practices and educate employees who utilize your respective RAIB process

Minimum Requirements

Degree or equivalent experience. Typically requires 12 years of professional experience and 4 years of management experience.

Critical Skills

• Proven experience designing implementing and scaling compliance programs for technology organizations
• Strong understanding of AI laws data protection laws and related regulatory frameworks with the ability to translate regulatory expectations into practical enterprise workflow.
• AI/ML Technical Fluency
• Understanding of AI/ML lifecycle model validation monitoring and documentation.
• Familiarity with GenAI/LLM risks (hallucination prompt injection etc) Knowledge of model risk management frameworks and risktiering logic.
• Ability to influence senior stakeholders (VP/EVP level) across business units.
• Strong changeleadership skills to drive adoption of governance processes.

We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors including performance experience and skills equity regular job market evaluations and geographical markets. The pay range shown below is aligned with McKessons pay philosophy and pay will always be compliant with any applicable regulations. In addition to base pay other compensation such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson pleaseclick here.

Our Base Pay Range for this position

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