Senior Director, AI Enablement

McKesson

. Define and own CoverMyMeds' AI enablement strategy and multi-year roadmap .

Posted 11/6/2026full-timeUnited StatesSenior💰 $174,800 - $291,300 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in AI strategy development, product delivery, and governance within regulated environments, ensuring compliance with HIPAA and privacy standards. Proven ability to lead cross-functional teams in building scalable AI solutions that drive measurable clinical and operational outcomes.

Highest-signal resume keywords

AI Strategy DevelopmentGenerative AI LeadershipAI Governance and ComplianceMulti-Agent Workflow DesignCloud-Native Architecture

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Software EngineeringAI Product DeliveryMachine LearningModel EvaluationPrompt EngineeringSpec-Driven DevelopmentCI/CDAutomated TestingData Quality ManagementHealthcare Interoperability Standards

Soft Skills

LeadershipCollaborationCommunicationBudget ManagementVendor Relationship Management

Tools & Technologies

GCPAWSMCPAI MarketplacesDevOpsGitHub CopilotClaudeModel Context ProtocolAPIsIntegration Platforms

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in a Technical Field or MBA (Preferred)

Industry Keywords

Healthcare TechnologyHIPAA CompliancePatient Data ProtectionAI AdoptionRegulated Environment

Tech Stack

Tools & technologies

AWSCloudCyber SecurityGoogle Cloud PlatformSDLC

About the role

Key responsibilities & impact

Define and own CoverMyMeds' AI enablement strategy and multi-year roadmap
Manage a portfolio of concurrent AI initiatives and a multimillion-dollar budget
Measure and report AI adoption, productivity, and ROI to executive leadership
Own the end-to-end build and delivery of AI products and agents
Champion agentic-native product and workflow design with humans in the loop
Partner with Product and business leaders to identify high-value use cases and deliver measurable clinical, operational, and financial outcomes
Use AI-accelerated delivery 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 integrated into AI development and delivery
Partner with Legal, Privacy, Security, and Compliance teams
Lead teams building reusable AI capabilities, including the AI Skills Marketplace, MCP servers, agents, and developer tooling
Advance the AI-embedded SDLC, including spec-driven development, AI code review, automated vulnerability remediation, shift-left testing, and self-service developer onboarding
Drive build-once, reuse-everywhere practices across teams and business units
Scale AI adoption across engineering, product, business, legal, finance, privacy, call center, and platform teams
Own the AI training curriculum and champions network
Advise senior leadership and the C-suite on AI strategy, capabilities, and risk
Build AI culture through townhalls, ERG sessions, and hands-on enablement
Partner with McKesson's Enterprise AI team and architecture, product, and platform leaders
Work with external technology partners and vendors
Hire, develop, and retain engineers, architects, and enablement specialists
Deliver agentic-native AI products, scalable governance, reusable AI assets, and regular executive reporting

Requirements

What you’ll need

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience
Typically requires 13+ years of relative software engineering and technology leadership experience
5+ years leading engineering or platform teams
3+ years of hands-on leadership in AI or ML, including generative AI, LLMs, and agentic AI in production environments
Proven track record of driving AI adoption at scale with measurable outcomes
Experience building and delivering AI-powered products or agents to production
Experience establishing AI governance, responsible AI practices, or technology standards in a regulated environment
Experience managing people, budgets, vendor relationships, and concurrent initiatives
Experience with generative and agentic AI, LLMs, RAG, agents, prompt and context engineering, model evaluation
Experience with multi-agent workflows, tool use, human-in-the-loop design, and agent observability and evaluation
Experience with product discovery, MVP definition, rapid iteration, and production release
Experience with MCP, reusable skills and plugins, AI marketplaces, and LLMOps
Knowledge of spec-driven development, CI/CD, DevOps, Cyber Security, automated testing, and code review
Knowledge of cloud-native architecture using GCP or AWS, APIs, and integration platforms
Knowledge of data quality, tagging, and synthetic data
Preferred: Master's degree in a technical field or an MBA
Preferred: Healthcare, pharmacy, or health technology experience, including HIPAA and patient data protection
Preferred: Experience with Claude, Claude Code, GitHub Copilot, Model Context Protocol, FHIR, healthcare interoperability standards, and matrixed enterprises

Benefits

Comp & perks

Competitive compensation package
Annual bonus may be offered
Long-term incentive opportunities may be offered
Benefits under McKesson's Total Rewards program
Equal employment opportunities
Reasonable accommodation for applicants with disabilities