AI Enablement Engineer

Our team members are at the heart of everything we do. At Cencora, we are united in our responsibility to create healthier futures, and every person here is essential to us being able to deliver on that purpose. If you want to make a difference at the center of health, come join our innovative company and help us improve the lives of people and animals everywhere.

This is best understood as an enterprise AI measurement, insights, and enablement role—not a model-building role. The core mandate is to empower Cencora’s employees to use AI responsibly, profitably, and well, and measure the value that AI adds to Cencora. While this role include various tasks related to AI enablement, such as community‑building, supporting responsible use, and participating in technology rollout efforts, a particular focus is to measure how AI adoption is impacting Cencora and translate results into decision‑ready insight for leaders.

The role blends measurement strategy, cross‑functional advisory work, and hands‑on analytics execution. Success depends on linking AI adoption and usage data to real business outcomes such as productivity, quality, cost reduction, risk reduction, proficiency, and change adoption rather than stopping at activity metrics alone.

The role’s central responsibility is to assist with AI enablement programs including the maturation of enterprise AI measurement framework covering: adoption engagement proficiency responsible use value realization ROI across multiple AI tools and platforms AI measurement framework design The role expects someone who can help define structured, reusable ways to measure AI adoption and value across the enterprise, including standard metric definitions and value hypotheses.

Hands‑on analytics and dashboarding This is not just a consulting role. It‑requires direct work with data, dashboard tools, KPI logic, reports, and visual storytelling. Executive communication and data storytelling A major requirement is turning complex metrics into clear narratives for senior leaders, while also being able to explain methods to practitioners and technical teams. Cross‑functional influence The person will likely need to drive alignment across business units, IT, governance, privacy, HR, and engineering without formal authority.

Business‑value and ROI thinking A candidate must be able to distinguish between usage metrics and business outcomes, and explain when value is direct, estimated, or better represented through proxies Change/adoption measurement Because the role sits within AI readiness and enablement, it values experience measuring proficiency, behavior change, and digital transformation outcomes Governance‑and privacy‑aware judgment Preferred experience in regulated or risk‑aware environments suggests strong relevance for privacy‑safe reporting, responsible use metrics, and collaboration with governance stakeholders.

Bachelor’s degree in computer science, data science, statistics, mathematics, engineering, information systems, or a related field, or equivalent experience required. Less than 2 years of experience in artificial intelligence, machine learning, data science, analytics, software development, or a related field, or equivalent experience required. Prior experience working with large data sets within an enterprise Prior experience and knowledge with AI Readiness, Enablement, AI Adoption, Engagement and Value Experience with Databricks – highly desired Excellent written & verbal communication skills Exceptional organizational skillsets.

Ability to support the following:
Define common KPI standards so business units are not measuring AI success inconsistently. Build dashboards, scorecards, and reporting…