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. Apply today!

Job Details

Summary:

This is best understood as anenterprise AI measurement, insights, and enablement role—not a model-building role. The core mandate is toempowerCencora’semployees to use AI responsibly, profitably, and well,and measurethe value that AI adds toCencora. Whilethis role includevarious tasks related toAI enablement,such as community-building, supportingresponsible use,and participating in technology rollout efforts,a particular focus is tomeasure how AI adoption is impacting Cencora andtranslate results into decision-ready insight for leaders. The role blendsmeasurement strategy, cross-functional advisory work, and hands-on analytics execution. Success depends on linking AI adoption and usage data toreal businessoutcomes such as productivity, quality, cost reduction, risk reduction,proficiency, and change adoption rather thanstopping atactivity metrics alone.

Responsibilities:

The role’s central responsibility is toassistwith AI enablement programs including thematuration ofenterprise AI measurement frameworkcovering:

- adoption

- engagement

- proficiency

- responsible use

- value realization

-
ROI across multiple AI tools and platforms

AI measurement framework design

-
The role expects someonewho canhelpdefine 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-requiresdirect 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 willlikely needto 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,itvalues experience measuringproficiency, behaviorchange, and digital transformation outcomes

Governance- and privacy-aware judgment

-
Preferred experience in regulated or risk-aware environments suggests strong relevance for privacy-safe reporting, responsibleusemetrics, and collaboration with governance stakeholders.

Toolsand methods:

The roleis likely to usea practical analytics stack rather than advanced model development tools. Based on the responsibilities, likely tools/methods include:

-
BI/dashboard toolssuch as Power BI orDatabricks AI/BI

-
Data warehousing tools including Databricks

- SQL and spreadsheet-based analysis

- PossiblyPython or Rfor deeper analysis

- Cross-platform telemetry / usage logs

-
Reporting feeds from AI tools, enablement systems, and business outcome systems

Qualifications :

-
Bachelor’s degree in computer science, data science, statistics, mathematics, engineering, information systems, or a related field, or equivalent experiencerequired.

-
Less than 2 years of experience in artificial intelligence, machine learning, data science, analytics, software development, or a related field, or equivalent experiencerequired.

-
Prior experience working with large data sets within an enterprise

-
Prior experience and knowledge with AI Readiness, Enablement, AI A