Senior Director, AI Enablement
About The Position
McKesson is seeking a Senior Director, AI Enablement to lead the next stage of CoverMyMeds’ AI transformation. The role owns AI strategy, governance, and AI engineering platforms for CoverMyMeds, and builds and delivers AI products using an agentic, AI-native approach. It scales safe, measurable AI adoption across engineering and business teams and partners with McKesson’s Enterprise AI team to create capabilities that can be reused across business units. This is a builder’s role combining technical depth, product delivery, strategic vision, and organizational change leadership. The Senior Director leads AI initiatives and platforms, develops products and agents from discovery through production and ongoing improvement, establishes responsible AI practices, and advises senior leaders on AI strategy, capabilities, and risk. The position also builds and develops a high-performing team and supports adoption across functions including product, business, legal, finance, privacy, call center, and platform teams. Success in the first year includes growing AI adoption across engineering and business functions; delivering agentic-native AI products to production with measurable outcomes; maintaining governance without slowing delivery; increasing reuse of AI assets across teams and business units; and providing regular executive reporting on adoption, productivity, and ROI.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience.
- Typically 13 or more years of relevant software engineering and technology leadership experience, including 5 or more years leading engineering or platform teams.
- At least 3 years of hands-on leadership in AI or ML, including generative AI, LLMs, and agentic AI in production environments.
- Proven record of driving AI adoption at scale with measurable outcomes in productivity, quality, or delivery speed.
- Demonstrated experience building and delivering AI-powered products or agents to production with measurable business impact.
- Experience establishing AI governance, responsible AI practices, or technology standards in a regulated environment.
- Experience managing people, budgets, vendor relationships, and a portfolio of concurrent initiatives.
- Knowledge of generative and agentic AI, including LLMs, RAG, agents, prompt and context engineering, and model evaluation.
- Knowledge of agentic-native product design, including multi-agent workflows, tool use, human-in-the-loop design, agent observability, and evaluation.
- Product delivery experience spanning discovery, MVP definition, rapid iteration, and production release.
- Knowledge of AI platform engineering, including MCP, reusable skills and plugins, AI marketplaces, and LLMOps.
- Knowledge of modern SDLC practices, including spec-driven development, CI/CD, DevOps, cybersecurity, automated testing, and code review.
- Knowledge of cloud-native architecture (GCP or AWS), APIs, and integration platforms.
- Knowledge of AI data foundations, including data quality, tagging, and synthetic data.
- Strategic vision and the ability to translate it into an executable roadmap.
- Executive communication and influence, including the ability to explain complex technical topics simply.
- Change leadership skills to help teams adopt everyday AI use.
- Cross-functional partnership skills with Legal, Privacy, Security, Product, and business leaders.
- Talent development skills and experience building inclusive, high-performing teams.
- Data-driven decision-making focused on measurable outcomes and ROI.
Nice To Haves
- Master’s degree in a technical field or an MBA.
- Healthcare, pharmacy, or health technology experience, including HIPAA and patient data protection.
- Experience with AI developer tooling such as Claude, Claude Code, GitHub Copilot, and Model Context Protocol (MCP).
- Experience with FHIR and healthcare interoperability standards.
- Experience in a matrixed, multi-business-unit enterprise.
Responsibilities
- Define and own CoverMyMeds’ AI enablement strategy and multi-year roadmap, aligned with business priorities and McKesson’s enterprise AI direction.
- Manage a portfolio of concurrent AI initiatives and a multimillion-dollar budget, prioritizing investments according to business value, risk, and reuse.
- Measure and report AI adoption, productivity, and return on investment to executive leadership.
- Own end-to-end development and delivery of AI products and agents, from discovery and design through production release and ongoing improvement.
- Design products and workflows around AI agents from the start, with human involvement where appropriate.
- Partner with Product and business leaders to identify high-value use cases and deliver products with measurable clinical, operational, and financial outcomes.
- Use AI-accelerated delivery to move ideas into production while maintaining quality, security, and compliance.
- Chair the AI Review Board and own AI usage policy, model-selection frameworks, token allocation, and cost management.
- Ensure HIPAA, privacy, and security requirements are incorporated into AI development and delivery processes.
- Partner with Legal, Privacy, Security, and Compliance to enable safe and responsible AI adoption.
- Lead teams building and operating reusable AI capabilities, including the AI Skills Marketplace, MCP servers, agents, and developer tooling.
- Advance the AI-embedded SDLC through spec-driven development, AI code review, automated vulnerability remediation, shift-left testing, and self-service developer onboarding.
- Promote build-once, reuse-everywhere practices for shared AI assets across teams and business units.
- Scale AI adoption across engineering and other functions, including product, business, legal, finance, privacy, call center, and platform teams.
- Own the AI training curriculum and champions network, spanning foundational AI literacy through advanced agentic workflows.
- Advise senior leadership and the C-suite on AI strategy, capabilities, and risk.
- Build an AI culture through town halls, ERG sessions, and hands-on enablement.
- Partner with McKesson’s Enterprise AI team and architecture, product, and platform leaders to align standards and avoid duplicate effort.
- Work with external technology partners and vendors to evaluate and adopt emerging AI capabilities.
- Hire, develop, and retain a high-performing team of engineers, architects, and enablement specialists.
Benefits
- Competitive compensation package as part of McKesson’s Total Rewards.
- Annual bonus or long-term incentive opportunities may be offered.
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What This Job Offers
Job Type
Full-time
Career Level
Director
