Director, Applied AI

Overview

The AI Center of Excellence (CoE) advances healthcare by applying data science and artificial intelligence to the enterprise’s highest‑value problems. As the central hub for AI at Cardinal Health, the CoE drives Enterprise AI Strategy, AI Enablement, AI Governance, and Enterprise AI Products. The Head of the CoE leads Applied AI engineering efforts, acting as the builder and execution engine for specific business use cases and partnering directly with internal business and IT stakeholders to deliver rapid proofs of concept and scale validated solutions.

• Partner with internal business and IT stakeholders to identify, shape, and prioritize high‑value AI use cases based on value, feasibility, and risk.
• Lead the delivery of those use cases as a player‑coach, shaping architecture, building or co‑building proofs of concept, and reviewing the team’s engineering work from idea through production.
• Move the strongest proofs of concept into scalable, supportable, production‑ready solutions rather than leaving them as isolated pilots.
• Build and promote reusable patterns, internal accelerators, and solution assets that scale across multiple business areas, reducing duplication and accelerating delivery.
• Transition matured solutions to delivery or run teams at the build‑to‑run handoff and redeploy the team to the next high‑value opportunity.
• Feed common needs and field learnings into the AI CoE product, engineering, and enablement roadmaps.
• Define the business case for AI initiatives: expected value, investment, delivery approach, adoption plan, and success metrics; support funding and prioritization discussions.
• Secure funding for high‑value AI initiatives by pitching business cases directly to executive sponsors.
• Connect each initiative to measurable outcomes: productivity, cost reduction, working capital, revenue, risk reduction, service quality, and patient or customer experience.
• Establish value‑tracking discipline, including baseline metrics, adoption measures, and business impact.
• Lead and develop AI engineers and AI engineering managers; set technical direction and standards for the team.
• Coordinate matrixed delivery across offshore engineering teams, contractors, vendors, and AI CoE partners; remove barriers, clarify ownership, and maintain momentum.
• Support executive updates, roadmap reviews, and decision‑making materials related to applied AI delivery and scaling.
• Ensure initiatives follow responsible AI, data protection, security, privacy, compliance, and governance expectations; partner with AI governance and risk teams to navigate review processes without slowing execution.
• Champion scalable, secure, and supportable solutions that can be reused across internal teams and business areas.

High‑value AI use cases proven and scaled into production; measurable business value delivered through AI initiatives; reuse and adoption of accelerators, patterns, and reusable capabilities across teams; reduced duplication of AI effort across the enterprise; stronger alignment between AI strategy, governance, delivery, and business outcomes.

• 10-12+ years of progressive experience in technology, data, AI, or product delivery, with 5+ years leading AI, machine learning, data science, analytics, or AI‑enabled engineering teams.
• Strong working knowledge of generative AI, machine learning, data platforms, and modern software delivery.
• Familiarity with the Google Cloud ecosystem (GCP, Vertex AI, Gemini suite of products) and Python.
• Player‑coach depth: able to shape solution architecture, prototype, and build proofs of concept, and review engineering work without requiring a full‑time individual contribution.
• Familiarity with LLMs, agentic AI, and AI product delivery is a plus.
• Highly flexible and able to span the enterprise; quick learner who balances priorities across all business units and effectively guides work.
• Exceptional solutioning skill set: ability to deliver creative solutions to complex problems.
• Demonstrated ability to engage business and IT leaders, understand their needs, shape use cases, and deliver tailored solutions that produce measurable outcomes.
• Experience building business…