Sr. Director, Enterprise AI Engagement

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 tomorrow’s health today, we want to hear from you.

We are seeking Sr. Director, Enterprise AI Engagement who acts as the front door to the enterprise AI practice—ensuring stakeholders have a clear path to engage, adopt, and scale AI capabilities across the organization.

Enterprise AI Adoption & Engagement Leadership

• Lead enterprise-wide AI adoption by establishing a scalable engagement model that serves as the front door to the enterprise AI practice.
• Build and operationalize learning, education, and enablement programs to upskill business and technology teams, accelerating AI fluency and usage across the organization.
• Partner with business and technology leaders to translate enterprise priorities into structured AI programs, ensuring alignment with strategic objectives and measurable outcomes.

AI PMO & Delivery Governance

• Own the enterprise AI Program Management Office (PMO), driving prioritization, roadmap alignment, and execution governance across AI engineering and solution delivery.
• Establish standardized operating rhythms, intake frameworks, and delivery processes to ensure transparency, speed, and consistency across the AI portfolio.
• Coordinate across data science, engineering, product, and business teams to ensure seamless execution and alignment on timelines, dependencies, and outcomes.

AI Product & Solution Enablement

• Oversee support models for enterprise AI products and solutions, ensuring reliability, scalability, and sustained adoption post-deployment.
• Define and implement frameworks for onboarding, user adoption, and lifecycle management of AI capabilities across business units.
• Partner with engineering and platform teams to ensure AI solutions are production-ready, maintainable, and aligned with enterprise standards.

Stakeholder Engagement & Enterprise Interface

• Act as the primary point of contact for stakeholders across the enterprise, providing a clear and consistent interface into the AI organization.
• Drive executive alignment and shared accountability across business and technology leaders to accelerate adoption and value realization.
• Navigate complex matrixed environments to align priorities, resolve conflicts, and ensure coordinated execution of AI initiatives.

Change Management, Learning & Culture

• Design and lead enterprise change management strategies to embed AI into decision-making and operational workflows.
• Establish continuous learning ecosystems, including training programs, playbooks, and communities of practice to scale AI knowledge and best practices.
• Foster a culture that balances speed, accountability, and continuous improvement, enabling teams to adopt and scale AI effectively.

Measurement, Reporting & Continuous Improvement

• Define and track KPIs for adoption, engagement, delivery performance, and business impact across the AI portfolio.
• Build transparent reporting mechanisms and executive-level dashboards to communicate progress, risks, and outcomes.
• Continuously refine engagement, delivery, and support models based on feedback and performance insights.

Minimum Requirement-Degree or equivalent experience. Typically requires 13+ years of professional experience and 6+ years of diversified leadership, planning, communication, organization, and people motivation skills (or 
equivalent experience)

Required Skills

• Proven ability to drive enterprise AI adoption through structured enablement, education, and stakeholder engagement models
• Strong experience building and running program management offices (PMOs) for complex, cross-functional technology initiatives
• Demonstrated success acting as a senior interface between business and technology, influencing executives and driving alignment
• Deep understanding of AI/ML lifecycle, with the ability to partner effectively with engineering and data science teams without owning model development directly
• Experience designi