Technical Program Manager – AI/ML Initiatives
Summary
Lead enterprise-scale AI/ML programs by defining strategic roadmaps, orchestrating cross-functional collaboration, and ensuring delivery excellence. Drive innovation while maintaining compliance and governance standards.
What You'll Do
Program Leadership & Road Mapping
Define and own the end-to-end roadmap for AI/ML initiatives, translating business objectives into actionable programs (e.g., demand forecasting models, LLM-driven chatbots, predictive analytics). Manage intake of new requests, validate business value, and ensure alignment with strategic priorities. Use portfolio tools (Jira, Confluence, MS Project, Smartsheet) to maintain visibility and alignment from ideation through deployment.
Cross-Functional Orchestration
Coordinate collaboration among data scientists, ML engineers, data engineers, business analysts, and IT teams. Ensure seamless integration of models into production systems via APIs, cloud ML services, and CI/CD pipelines.
Execution & Delivery Management
Oversee day-to-day delivery using Agile practices (Scrum, SAFe, Kanban). Manage sprints, backlogs, and dependencies in Jira/Confluence. Identify risks (data gaps, performance issues, infrastructure bottlenecks) and implement mitigation strategies. Enforce testing standards (unit tests, model validation, A/B testing, benchmarking).
Business Alignment & Stakeholder Management
Translate business use cases into technical AI/ML requirements. Partner with leaders to define KPIs (accuracy, ROI, adoption). Provide executive-level updates and manage expectations while balancing speed, compliance, and ethics.
Governance & Compliance
Ensure adherence to frameworks (HIPAA, GDPR, SOC 2, FDA). Promote Responsible AI principles (fairness, transparency, explainability). Maintain documentation, data lineage, and reproducibility. Standardize MLOps governance (model versioning, drift monitoring, automated retraining).
Metrics & Reporting
Define and track KPIs across technical and business dimensions (accuracy, precision/recall, F1 score, ROI, cost reduction). Provide transparent reporting on portfolio health and program success.
Innovation Enablement
Drive adoption of emerging technologies (Generative AI, LLMOps, AutoML). Collaborate on modernizing ML stack (Databricks, Vertex AI, Azure ML). Promote accelerators (code libraries, pre-trained models, standardized pipelines) to reduce time-to-market.
What You Bring
- Proven experience in technical program management for AI/ML initiatives.
- Strong understanding of Agile methodologies and portfolio management tools.
- Expertise in AI/ML technologies, MLOps practices, and cloud platforms.
- Ability to translate business objectives into technical deliverables.
- Excellent stakeholder management and communication skills.
Minimum Requirements
- Degree or equivalent and typically requires 10+ years of relevant experience. Less years required if has relevant Master's or Doctorate qualifications.
Preferable Skills & Experience
- Familiarity with regulatory compliance for AI/ML (HIPAA, GDPR).
- Experience with Generative AI, LLMOps, and AutoML.
- Knowledge of advanced ML platforms (Databricks, Azure ML, Vertex AI).
- Strong background in risk management and governance for AI systems.
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are a diversified healthcare services leader that strives to fulfill our purpose of Advancing Health Outcomes For All® by making quality care more accessible and affordable. Guided by our values, we are an impact-driven organization that improves care in every setting – one product, one partner, one patient at a time.
April 10, 2026
5-7 business days
After submission
- •Explicit, repeated references to applied AI technologies (LLMs, Generative AI, LLMOps, AutoML) and named platforms (Databricks, Azure ML, Vertex AI).
- •Clear emphasis on workflow integration and productionization: APIs, CI/CD, model versioning, drift monitoring, automated retraining, and MLOps governance.
- •Strong strategic remit: owning roadmaps, validating business value, defining KPIs (accuracy, ROI, adoption), and stakeholder/executive reporting.
This senior TPM role at a large, stable healthcare company provides strong evidence of compensation, organizational stability, high ownership, regulatory focus, and technical depth (MLOps, cloud, Generative AI). Lower-level needs are partially met (salary and full-time status are explicit, but benefits details are missing). The role scores highly for safety and esteem due to company stability and high visibility; self-actualization and belonging are present but lack explicit signals about formal development programs and inclusive culture practices. Candidates should clarify team resourcing, benefits/total rewards, and expected workload boundaries.
- •No explicit mention of core employee benefits (health/dental/vision, retirement/401k/CPP matching, paid time off) in the posting — candidates should confirm total rewards.
- •Scope and resourcing are unclear: job asks for end-to-end ownership across strategy, delivery, governance, and innovation without stating team size or dedicated engineering/MLOps support — risk of an oversized individual scope.
- •Workload and work-life balance expectations are not defined (no mention of typical hours, on-call, or boundaries) despite high-stakes, cross-functional, and compliance-sensitive responsibilities.
- •Clear salary range: $113,500 - $189,100 / year (explicit).
- •Employer is an established Fortune 10 company (McKesson) — strong signal of organizational stability.
- •Role explicitly owns end-to-end AI/ML program roadmaps and executive stakeholder management — high visibility and ownership.
- •Who will I report to, and what is the size and composition of the team(s) supporting AI/ML programs (data scientists, ML engineers, MLOps, product owners)?
- •How are AI/ML programs resourced and prioritized — how many concurrent programs would a TPM typically own and is there dedicated engineering/ops support for productionization?
- •What formal professional development resources exist for this role (training budget, conference allowance, time for upskilling, mentorship or career ladders for TPMs working on AI/ML)?
Location
Salary Range
$114k - $189k
Employment Type
Full-time
Experience Level
Senior
Posted
January 10, 2026 (2 weeks ago)
3 Simple Steps
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