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About This Role
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.
This role offers location flexibility and is open to candidates across the United States.
Candidates based in the Dallas–Fort Worth (DFW) area will be hired in a hybrid capacity and are expected to work onsite at our Las Colinas office a minimum of two (2) days per week, with the remaining days worked remotely. Specific in‑office days may be designated based on team needs and business priorities.
About the Role:
The Senior Technical Product Manager, AI & Analytics will lead the product strategy, roadmap, and delivery of AI, automation, analytics, and intelligent workflow capabilities across the pharmacy management and Data & Insights platforms.
As part of the Data Strategy & Analytics function, this role will translate customer needs, pharmacy workflows, modernization priorities, and business objectives into scalable product capabilities, clear requirements, prioritized roadmaps, and measurable outcomes.
Working across Engineering, Architecture, Data Science, UX, Compliance, Commercial, and Pharmacy Operations, the role will embed actionable insights into pharmacy workflows to improve operational performance, customer experience, and business value. It will also guide the evolution of the Data & Insights Platform into a cloud-native, AI-ready platform delivering governed, scalable data products across EnterpriseRx, CPS, APS, Supplylogix, and future product portfolios.
The Senior Technical Product Manager, AI & Analytics will lead the product strategy and roadmap for the Data & Insights Platform, embedding AI and advanced analytics into the pharmacy platform as core capabilities. This role will translate customer and business needs into scalable solutions that support platform modernization, intelligent insights, workflow innovation, and measurable business value.
What You'll Do:
Lead the Data & Insights Platform Product Strategy
- Define and drive the platform vision, strategy, roadmap, and outcomes aligned with Pharmacy Systems modernization and the Pharmacy Operating System strategy.
- Evolve the platform into a cloud-native, AI-enabled analytics product that balances scalability, reliability, governance, security, performance, and cost efficiency.
- Lead product strategy for reporting, analytics, self-service insights, data products, AI-powered experiences, and customer-facing intelligence.
- Prioritize Snowflake optimization, governed data access, semantic models, auditability, data quality, lineage, and service-level management.
- Establish unified analytics and data product capabilities across EnterpriseRx, CPS, APS, and Supplylogix to enable governed, cross-domain insights.
- Partner with customers, pharmacy SMEs, UX, Commercial teams, and Product Owners to identify high-value opportunities and translate them into measurable outcomes.
- Define product requirements, MVP scope, user stories, acceptance criteria, KPIs, and success measures.
- Own roadmap and backlog prioritization informed by customer feedback, market analysis, business value, and technical feasibility.
- Partner with Commercial and Finance teams on packaging, entitlements, adoption, monetization, cost-to-serve, and value realization.
- Lead design-partner engagements, pilots, product launches, and go-to-market readiness.
Define the AI Product Vision and Roadmap
- Develop the AI strategy and roadmap for the Data & Insights Platform and broader Pharmacy Operating System.
- Identify opportunities to automate workflows, improve decisions, enhance user experiences, and increase operational efficiency.
- Translate modernization objectives into scalable AI-enabled capabilities that create customer and business value.
- Ensure AI solutions align with platform principles for scalability, configurability, multi-tenancy, security, governance, and reuse.
- Establish requirements for explainability, responsible AI, monitoring, user feedback, adoption, and trustworthy outputs.
- Partner with Product, Engineering, Architecture, and Data Science teams to validate, prioritize, and scale AI capabilities.
Drive Cross-Functional Product Delivery
- Serve as the Product Management lead for data, analytics, reporting, and AI platform capabilities.
- Collaborate with Engineering, Architecture, UX, Data Strategy, Security, Compliance, Commercial, and Pharmacy Operations to deliver roadmap commitments.
- Define functional and non-functional requirements for analytics and AI-enabled workflows.
- Ensure solutions are scalable, configurable, secure, multi-tenant, and operationally resilient.
- Lead backlog prioritization, sprint planning, UAT, release readiness, and delivery governance.
- Align platform capabilities with APIs, event-driven architecture, domain-driven design, and reusable platform services.
- Monitor adoption, performance, customer outcomes, and product value to guide continuous improvement.
Basic Requirements:
- Degree or equivalent and typically requires 7+ years of relevant experience.
- 7+ years of experience in Product Management, Technical Product Management, Platform Product Management, or Product Strategy.
- Experience leading complex SaaS, enterprise software, workflow, healthcare technology, or data platform products.
- Strong understanding of AI/ML, GenAI, automation, analytics, and data products from a product management perspective.
- Ability to translate technical and AI concepts into customer-facing capabilities, roadmaps, and measurable business outcomes.
- Experience partnering with Engineering, Architecture, UX, Data, Analytics, Security, Compliance, and Commercial teams.
- Experience managing analytics, reporting, dashboard, visualization, self-service, or cloud data platform products.
- Strong skills in product discovery, roadmap development, backlog prioritization, MVP definition, user stories, acceptance criteria, and success metrics.
- Experience operating in complex, regulated enterprise environments.
- Excellent executive communication and stakeholder management skills.
- Proven ability to influence and align cross-functional teams without direct authority.
Preferred Skills/Experience:
- Experience with pharmacy management systems, healthcare technology, pharmacy operations, claims, adjudication, inventory management, or clinical workflows.
- Experience with Snowflake, Looker, or comparable cloud data and business intelligence platforms, including governed analytics, query optimization, workload management, and cost controls.
- Experience launching AI-powered products, workflow automation, copilots, recommendation engines, or decision-support tools.
- Familiarity with product telemetry, usage analytics, experimentation, and outcome measurement.
- Experience developing customer-facing analytics, self-service insights, or data monetization strategies.
- Knowledge of modern data architecture, data governance, and AI governance practices.
Physical Requirements:
- Will require up to 10% travel.
Candidates within a 50-mile radius of Irving, TX will be required to be onsite 2 days per week. *
McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role.
Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g., H1B, O1, E3, H1B1, TN, F1 OPT, F1 STEM OPT, F1 CPT, etc.) now or in the future.
If you will require McKesson to provide immigration support or sponsorship now or in the future, you should not apply for this position.
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 McKesson's 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,
Our Base Pay Range for this position
$116,200 - $193,600 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson’s (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind:
McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application.
McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates.
McKesson job postings are posted on our career site: careers.mckesson.com.
McKesson is an Equal Opportunity Employer
McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson’s full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page.
McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) [email protected] or (Canada) [email protected]. Resumes or CVs submitted to this email box will not be accepted.
Join us at McKesson!
Benefits
*
Coverage you can rely on
+ Medical, Dental, and Vision + Health Spending Accounts + Flexible Spending Accounts *
Benefits that go beyond your base pay
+ 401(k) (U.S.) + Pension (Canada) + Employee Stock Purchase Plan *
Support for total well-being
+ Mental Health Programs + Flexible Schedules + Paid Time Off + Wellness Program + Education Reimbursement + Volunteer Opportunities + Flexible Work Environment *
A culture powered by belonging
By fostering a culture of belonging, we advance our goal of being the best place to work in healthcare—connecting the right talent to the right roles to solve our most critical challenges.
Salary Context
This $116K-$193K range is below the median for AI Product Manager roles in our dataset (median: $187K across 155 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 11,520 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At McKesson, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $220,200 based on 993 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($154K) sits 30% below the category median. Disclosed range: $116K to $193K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
McKesson AI Hiring
McKesson has 8 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, AI Product Manager. Positions span Richmond, VA, US, Columbus, OH, Columbus, OH, US. Compensation range: $175K - $200K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 roles, $210,000 median).
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (140) are outnumbered by mid-level (5,630) and senior (4,176) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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