Lead Program Manager, Oncology and Multi Specialty Technology Strategy

Position Summary

The Lead Program Manager, Oncology and Technology Strategy leads the operational delivery and continued maturation of McKesson's Responsible AI Board (RAIB) governance program within the Oncology and Technology Strategy organization. The role translates Responsible AI policy, RAIB Charter requirements, and business priorities into an executable program roadmap, governance structure, operating cadence, service-level expectations, and measurable outcomes. Partnering with business and technology leaders, Responsible AI Owners, Legal, Compliance, Privacy, Information Security, Architecture, Data, and other control functions, this role manages the full AI Use Case lifecycle across multiple related governance activities.

The Lead Program Manager drives cross-functional alignment, manages program-level risks and dependencies, resolves escalated issues, and maintains visibility into portfolio health, decision quality, control implementation, and ongoing monitoring. This is a hands‑on program leadership role with accountability for program outcomes rather than only process administration. Success requires the autonomy to lead complex work, influence without direct authority, establish scalable standards, challenge inefficient ways of working, and use analytics and automation to strengthen executive decision-making.

Break down Responsible AI program objectives into measurable business and technology outcomes, and maintain a program roadmap that translates governance requirements into executable plans, milestones, deliverables, and success measures. Lead the end-to-end AI Use Case governance lifecycle across intake, triage, RAIB Operations quality review, RAIB and EAIC review, final decision, control implementation, and ongoing monitoring. Partner with program sponsors and senior stakeholders to align governance priorities, secure support, resolve high visibility issues, and ensure the program continues to deliver enterprise value.

Establish and maintain the program governance structure, operating cadence, decision rights, escalation paths, service-level objectives, and delivery standards consistent with McKesson's Responsible AI Program, Responsible AI Policy, and RAIB Charter. Identify, consolidate, and manage program-level risks, issues, interdependencies, and resource constraints across governance activities; develop mitigation plans, assign accountable owners, and escalate significant risks with recommended actions. Lead scope, priority, and risk trade-off discussions with stakeholders, driving consensus while preserving policy, control, documentation, and audit requirements.

Ensure governance records, risk assessments, approvals, conditions, controls, and notifications are complete, accurate, timely, and audit-ready.

Lead preparation and execution of RAIB sessions and, when required, EAIC secondary reviews in partnership with the RAIB Operations and Governance Lead and Sr. Product Portfolio Manager. Ensure review materials enable informed decisions and that every decision, condition, action, owner, and due date is documented accurately in Smartsheet and communicated within the required response window. Serve as the first escalation path for at-risk submissions, unresolved information gaps, missed commitments, or stakeholder conflicts that could affect governance quality, cycle time, or program outcomes.

Act as a trusted program advisor to business and technology stakeholders, translating Responsible AI requirements into clear actions, decision points, and ownership expectations. Build and maintain strategic cross-functional relationships, establish effective feedback loops, and lead regular interactions with sponsors and stakeholders to inform, alert, negotiate, and drive timely resolution. Influence adoption of Responsible AI governance practices without direct authority through clear communication, consultation, education, and disciplined follow-through.

Define, maintain, and report program KPIs and service-level measures, including submission volume, risk-tier trends, cycle time, backlog health, control status, decision timeliness, and stakeholder responsiveness. Develop executive-ready dashboards, scorecards, forecasts, and portfolio health reporting that convert governance data into actionable insights, risks, decisions, and improvement priorities. Work with sponsors to assess program effectiveness, stakeholder satisfaction, and realized business value; recommend adjustments that improve quality, throughput, transparency, and scalability.

Use automation, analytics, and AI-enabled insights where appropriate to improve forecasting, identify emerging risks, strengthen prioritization, and reduce manual reporting effort.

Lead…