Director, AI Engineering

McKesson•Alpharetta, GA

1d•$196,100 - $326,900

About The Position

The Director leads major divisional functions or corporate sub-functions, providing enterprise-level strategic direction, long-range planning, and operational leadership across related disciplines. The role analyzes external business environments to anticipate trends, influence strategy, and recommend growth opportunities. It directs managers to ensure operational excellence, cross-functional integration, and delivery of high-impact initiatives, and is financially accountable for operating plans, budgets, and forecasts. As a senior enterprise advisor, the Director works with leaders to shape integrated business strategies and align products, solutions, and capabilities with organizational priorities. The role leads talent pipelines, strengthens leadership benches, manages significant conflicts and disciplinary matters, drives continuous improvement, optimizes workflows, and ensures strategic communication across stakeholder groups. The Director of AI Engineering leads AI/ML engineering organizations through a management layer, owns operating budgets and forecasts, and provides technical direction on AI/ML systems, including machine-learning lifecycles, data architecture, and large language model deployment. The position translates business strategy into multi-year technical roadmaps and is accountable for execution in a regulated, high-compliance enterprise environment. It partners across Product, Data Engineering, Platform/Infrastructure, Security, Legal/Compliance, and business-unit leadership, while managing vendors, performance frameworks, service-level agreements, and continuous improvement.

Requirements

Degree or equivalent experience.
Typically 12 or more years of professional experience and 4 or more years of management experience.
At least 5 years of experience in Responsible AI practices, model risk management, data governance, and audit readiness.
Proven experience leading AI/ML engineering organizations through a management layer, including people management.
Experience owning and growing an operating budget and forecast.
Deep technical credibility in AI/ML systems, including machine-learning lifecycle, data architecture, and large language model deployment at scale.
Experience operating in a regulated or high-compliance enterprise environment.
Track record of translating business strategy into a multi-year technical roadmap and accountability for execution.
Experience partnering with Product, Data Engineering, Platform/Infrastructure, Security, Legal/Compliance, and business-unit leaders.
Experience with enterprise-scale cloud AI/ML platforms and production-scale tools or technologies such as Azure services, LangChain/LangGraph, and Python.
Experience with succession planning, performance calibration, significant conflict, and disciplinary matters.
Vendor and partner management experience, including build-versus-buy analysis and cloud/AI vendor negotiations.
Experience establishing KPI/metrics frameworks, managing service-level agreements, and applying continuous improvement methodologies.
Experience supporting multiple business units, product lines, or customer segments concurrently.
Must be authorized to work in the United States now or in the future without support from McKesson.

Nice To Haves

Expertise in healthcare, pharmaceutical distribution, or supply chain.

Responsibilities

Lead AI/ML engineering organizations through a management layer, including people management.
Own and grow operating budgets and forecasts.
Provide technical leadership and make build-versus-buy and architecture decisions for AI/ML systems.
Translate business strategy into multi-year technical roadmaps and lead their execution.
Partner with Product, Data Engineering, Platform/Infrastructure, Security, Legal/Compliance, and business-unit leaders.
Lead succession planning, performance calibration, and the handling of significant conflicts and disciplinary matters.
Manage vendors and partners, including build-versus-buy analysis and cloud/AI vendor negotiations.
Establish KPI and metrics frameworks and manage service-level agreements across services and programs.
Drive continuous improvement across multiple business units, product lines, or customer segments.
Lead major divisional functions or corporate sub-functions, direct managers, and ensure operational excellence and cross-functional integration.
Provide enterprise-level strategic direction, long-range planning, and operational leadership.
Analyze external business environments, anticipate trends, influence strategy, and recommend growth opportunities.
Manage operating plans, budgets, forecasts, and organizational performance across services.
Advise enterprise leaders on integrated business strategies and alignment of products, solutions, and capabilities with organizational priorities.
Lead talent pipelines, strengthen leadership benches, optimize cross-functional workflows, and ensure strategic communication across stakeholder groups.