Job Description

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 solid 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.

📌 AI Enablement & Governance Analyst (Pune)
🏢 EVERSANA
📍 Pune