Director, Applied AI
$135.4k - $208.1kCardinal Health
What the AI Center of Excellence contributes to Cardinal Health
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 artificial intelligence at Cardinal Health, the CoE drives Enterprise AI Strategy, AI Enablement, AI Governance, and Enterprise AI Products in close partnership with technology and business leaders across the company. Through these pillars, we collaborate to build and scale reusable patterns, internal accelerators, and responsible AI practices, turning data into solutions that improve patient and customer outcomes, streamline operations, reduce cost, and strengthen the overall healthcare experience.
Reporting to the Head of the AI Center of Excellence, this role leads our Applied AI engineering efforts. While our AI Product leaders own the long term enterprise capabilities, this role acts as the "builder and execution engine" for specific business use cases. The operating model is deliberately structured as an internal, forward deployed capability: your team will partner directly with various business and IT stakeholders across the company to prove use cases through rapid proofs of concept, move the strongest into production, transition matured solutions to delivery or run teams, and immediately redeploy to the next high value internal opportunity. This keeps the team continuously focused on what is unproven and most valuable next, turning field learnings into reusable enterprise capabilities.
Location - Open to candidates based nationwide (with willingness to travel quarterly into our global headquarters in Dublin, Ohio)
Responsibilities
Forward Deployed Use Case Delivery: 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.
Reusable Capabilities and Scaling: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.
Stakeholder Partnership and Business Value: Define the business case for AI initiatives: expected value, investment, delivery approach, adoption plan, and success metrics, and support funding and prioritization discussions.
Secure funding for high value AI initiatives by pitching business cases directly to executive sponsors.
Connect every 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.
Team Leadership and Execution: 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 practical execution.
Champion scalable, secure, 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.
Quality and growth of stakeholder partnerships and the funding pipeline.
Stronger alignment between AI strategy, governance, delivery, and business outcomes.
Qualifications
Ideally targeting individuals with 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.
Technical Skills & Tech Stack: 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 is highly desirable. Player coach depth, able to shape solution architecture, prototype and build proofs of concept, and review engineering work without requiring full time individual contribution. Familiarity with LLMs, agentic AI, and AI product delivery is a plus.
Adaptability & Continuous Learning: Highly flexible and able to span the enterprise. Your team could deploy into any internal business unit, so this leader must learn quickly, balance priorities across all businesses, and know enough to effectively guide the work.
Problem Solving & Solutioning: Exceptional solutioning skill set. Stakeholders will come to this team for help solving complex problems that their teams may not be able to do themselves, so having the ability to help offer up creative solutions is important.
Customer Facing & Stakeholder Skills: 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 cases and supporting funding and prioritization decisions.
Excellent written and verbal communication, facilitation, and executive presentation skills, with the ability to translate complex AI concepts into practical business and delivery guidance.
Leadership: Demonstrated ability to lead and develop technical teams, direct senior individual contributors, and coordinate matrixed resources across offshore teams, contractors, and vendors on multiple high priority initiatives.
Experience with AI Centers of Excellence, enterprise AI platforms, reusable AI patterns, internal accelerators, and AI product adoption a plus.
Track record of scaling AI initiatives from proof of concept into production and broad adoption.
Strong product mindset, connecting stakeholder needs to reusable enterprise capabilities.
Experience operating in an embedded, internal forward deployed, or field technology leadership model.
#LI-LP
#LI-Remote
Anticipated salary range: $135,400 - $208,100
Bonus eligible: Yes
Benefits: Cardinal Health offers a wide variety of benefits and programs to support health and well-being.
Medical, dental and vision coverage
Paid time off plan
Health savings account (HSA)
401k savings plan
Access to wages before pay day with myFlexPay
Flexible spending accounts (FSAs)
Short- and long-term disability coverage
Work-Life resources
Paid parental leave
Healthy lifestyle programs
Application window anticipated to close: 07/15/2026 *if interested in opportunity, please submit application as soon as possible.
The salary range listed is an estimate. Pay at Cardinal Health is determined by multiple factors including, but not limited to, a candidate's geographical location, relevant education, experience and skills and an evaluation of internal pay equity.
Candidates who are back-to-work, people with disabilities, without a college degree, and Veterans are encouraged to apply.
Cardinal Health supports an inclusive workplace that values diversity of thought, experience and background. We celebrate the power of our differences to create better solutions for our customers by ensuring employees can be their authentic selves each day. Cardinal Health is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law.
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