AI Enablement & Governance Analyst

The AI Adoption & Governance Analyst operationalizes AI standards across the Patient Services engineering organization and proves the SDLC transformation in metrics. This role is the connective tissue of the AI Hub COE: rolling out AI development tooling to Dev, QA, and BA teams; owning the governance artifacts that keep AI use safe and compliant; and reporting the adoption and ROI story to leadership.

It is the right role for someone who blends analytical rigor with strong communication and change-management instincts - someone who can drive real adoption of new ways of working, not just publish a policy.

Mission: Operationalize AI standards across BA, QA, and Dev - and prove the SDLC transformation in measurable adoption and ROI.

Key Responsibilities:

Adoption & Enablement

• Roll out AI development tooling - Claude Code, GitHub Copilot, Cursor - as engineering standards across the Patient Services teams.
• Train and onboard Dev, QA, and BA staff into AI-augmented ways of working; run office hours, certification, and internal forums.
• Own the AI best-practice wiki, training materials, and the agent registry.

Governance & Compliance

• Own and maintain the prompt library governance process, including quality gates before templates are promoted.
• Conduct HIPAA/PHI compliance reviews of AI tool usage; coordinate with InfoSec on data-flow approval and risk sign-off.
• Maintain the approved-tools list and the AI risk register.
• Support model-selection and BAA-verification processes led by the AI Engineering & Enablement Lead.

Metrics & Reporting

• Define and track AI adoption KPIs: AI velocity, code-generation percentage, defect-rate delta, time-to-merge, and story points per sprint.
• Author monthly team adoption reports and quarterly executive ROI dashboards for the CTO and CFO.
• Surface adoption gaps and recommend interventions to the AI Engineering & Enablement Lead. Qualifications

Required Qualifications:

• 3+ years in a technical analyst, program enablement, developer-experience, or similar role.
• Strong data analysis and dashboarding skills.
• Excellent technical writing and documentation ability.
• Demonstrated change-management and training-delivery experience.
• Working fluency with AI tooling ecosystems (Claude, Gemini, AI coding assistants) - able to teach and support their use.
• Understanding of HIPAA, SOC 2, or comparable privacy/compliance fundamentals.
• Strong cross-team coordination and stakeholder-communication skills.

Preferred Qualifications

• Background in healthcare or life-sciences technology.
• Experience supporting or governing an AI or developer-tooling rollout at scale.
• Familiarity with JIRA, Confluence, and BI tools (Looker, Tableau, or BigQuery).

Tools & Stack

• AI (evaluation & support): Claude, Gemini Enterprise, Einstein.
• Dev tools supported: Claude Code, GitHub Copilot, Cursor.
• Dashboards & data: Looker / Tableau, BigQuery.
• Documentation: Confluence, Notion, JIRA.

First-Year Success Measures

• AI development tooling adopted across Patient Services engineering, with measurable AI velocity gains tracked and reported.
• Governance framework operational: approved-tools list, prompt-library process, risk register, and compliance-review workflow all live.
• Monthly adoption reporting and quarterly executive ROI dashboards established and delivered.