✦ Luna Orbit — AI & Machine Learning

Lead Technical Product Manager - Finance AI

at McKesson

📍 2 Locations Hybrid 💰 $136K – $227K USD / year Posted April 14, 2026
Salary $136K – $227K USD / year
Type Full-Time
Experience lead
Exp. Years Not specified
Education Not specified
Category AI & Machine Learning

This role leads AI-powered product strategy and execution for Finance AI across Oncology & Multispecialty (O&M) Finance. The Lead TPM owns the roadmap, defines success metrics and requirements, and partners with analytics and engineering teams to deliver scalable AI-enabled finance capabilities.

  • Own and evolve the AI for O&M Finance product roadmap, Convert business problems into project charters, success metrics, user stories, and technical requirements, Lead AI initiative scoping with value hypotheses and delivery readiness criteria, Guide technical implementation roadmap with data science and engineering, Drive agile collaboration through sprint planning, standups, and retrospectives

The technical scope centers on AI/ML concepts, data pipelines, APIs, and cloud platforms to guide solution design and implementation. The Lead TPM collaborates with data science and engineering to ensure feasibility, scalability, and architectural standards while running agile delivery activities like sprint planning and retrospectives.

The ideal candidate is a Lead Technical Product Manager (TPM) with strong AI/ML product experience who can own an AI roadmap for finance operations. They convert ambiguous problems into project charters, success metrics, user stories, and technical requirements, and they maintain enough technical depth across data pipelines, APIs, and cloud platforms to partner effectively with data science and engineering teams.

Deep technical acumen in data science and AI/MLOwn and evolve the AI for O&M Finance product roadmapTranslate business needs into AI-enabled finance capabilitiesConvert ambiguous business problems into well-defined project charterssuccess metricsuser storiesand technical requirementsMaintain sufficient technical depth across AI/ML conceptsdata pipelinesAPIsand cloud platformsLead prioritization decisions across competing initiatives by balancing business valuefeasibilityeffortand risk
Lead Technical Product ManagerTechnical Product Manager (TPM)AIpowered productsAI-enabled finance capabilitiesproduct roadmapproject charterssuccess metricsuser storiestechnical requirementsuse case scope boundariesvalue hypothesesdelivery readiness criteriapost-deployment success metricsprioritization decisionsdata scienceengineering collaborationsprint planningstandupsretrospectivesAI/ML conceptsdata pipelinesAPIscloud platformsstakeholder engagementcustomer feedback loops
AIpowered productsAI for O&M Finance product roadmapproduct roadmap ownershipsuccess metrics definitionuser storiestechnical requirementsproject chartersideation workshopsdiscovery workshopscontinuous improvement workshopsautomation opportunities identificationuse case scope boundariesvalue hypothesesdelivery readiness criteriapost-deployment success metricsprioritization decisionstechnical implementation roadmapdata science collaborationengineering collaborationarchitectural standards alignmentsprint planningstandupsretrospectivesAI/ML conceptsdata pipelinesAPIscloud platformsstakeholder managementcustomer feedback loopscross-functional influence
influencing cross-functional teams without direct authoritycritical thinkingcross-functional collaborationrelationship buildingtrust-based stakeholder engagementcommunicationleadershipworkshop facilitationdecision-making
Industry Healthcare IT
Job Function Lead AI/ML finance product strategy and delivery as a technical product manager.
Role Subtype Technical Product Manager
Lead Technical Product ManagerLead Technical Product Manager - Finance AITechnical Product Manager (TPM)AIAIpowered productsAIenabled financeproduct roadmapproject charterssuccess metricsuser storiestechnical requirementsuse case scope boundariesvalue hypothesesdelivery readiness criteriapost-deployment success metricsprioritization decisionsbusiness valuefeasibilityeffortrisktechnical implementation roadmapdata scienceengineeringarchitectural standardssprint planningstandupsretrospectivesAI/ML conceptsdata pipelinesAPIscloud platformsstakeholder engagementcustomer feedback loopscross-functional influenceFinance OperationsAI for O&M Finance product roadmap

Must have deep technical acumen in data science and AI/ML, Must be able to maintain technical depth across AI/ML concepts, data pipelines, APIs, and cloud platforms

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