AI Enablement Engineer

Summary

Cencora is committed to creating healthier futures and improving the lives of people and animals everywhere. The AI Enablement Engineer will support enterprise AI measurement, insights, and enablement by developing measurement frameworks, analyzing adoption and business value, creating dashboards, and translating results into decision-ready insights for leaders. The role also involves cross-functional collaboration, responsible AI use, governance, privacy, and ROI analysis.

Responsibilities

• Adoption
• Engagement
• Proficiency
• Responsible use
• Value realization
• ROI across multiple AI tools and platforms
• 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
• This is not just a consulting role. It -requires direct work with data, dashboard tools, KPI logic, reports, and visual 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
• The person will likely need to drive alignment across business units, IT, governance, privacy, HR, and engineering without formal authority
• 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
• Because the role sits within AI readiness and enablement, it values experience measuring proficiency, behavior change, and digital transformation outcomes
• Preferred experience in regulated or risk-aware environments suggests strong relevance for privacy-safe reporting, responsible use metrics, and collaboration with governance stakeholders
• BI/dashboard tools such as Power BI or Databricks AI/BI
• Data warehousing tools including Databricks
• SQL and spreadsheet-based analysis
• Possibly Python or R for deeper analysis
• Cross-platform telemetry / usage logs
• Reporting feeds from AI tools, enablement systems, and business outcome systems
• Define common KPI standards so business units are not measuring AI success inconsistently
• Build dashboards, scorecards, and reporting that show what is being adopted, where usage is growing or lagging, and whether AI is creating business value
• Analyze trends and gaps to recommend actions for enablement, governance, and investment decisions
• Partner across matrixed stakeholders to define meaningful success measures for specific AI initiatives
• Develop ROI/value methods that connect AI to measurable business outcomes such as time saved, throughput, quality gains, reduced errors, avoided risk, or cost savings
• Maintain an enterprise view across multiple tools and use cases, not just isolated reporting for one platform

Skills

• 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
• Excellent written & verbal communication skills
• Exceptional organizational skillsets
• Experience with Databricks - highly desired

Qualifications

Must Haves

• 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
• Excellent written & verbal communication skills
• Exceptional organizational skillsets

Nice to Haves

• Experience with Databricks - highly desired

Benefits

• Medical, dental, and vision care
• Backup dependent care
• Adoption assistance
• Infertility coverage
• Family building support
• Behavioral health solutions
• Paid parental leave
• Paid caregiver leave
• Training programs
• Professional development resources
• Opportunities to participate in mentorship programs
• Employee resource groups
• Volunteer activities