AI Enablement & Governance Analyst

IndiaRemoteFull-timemid

Other

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Quick Summary

Key Responsibilities

Drive AI adoption and enablement: Coordinate the rollout of AI development tools, including Claude Code, GitHub Copilot, and Cursor, across Development, QA, and Business Analysis teams.

Requirements Summary

At least 3 years of experience in a technical analyst, program enablement, developer experience, or related role. Strong data analysis and dashboarding capabilities,

Technical Tools

Other

We are seeking an AI Enablement & Governance Analyst to accelerate the adoption of AI-powered development practices across a healthcare technology organization. In this role, you will help engineering, QA, and business analysis teams integrate AI tools into their daily workflows while ensuring responsible, secure, and compliant usage. You will coordinate training initiatives, maintain governance frameworks, and establish standards that support consistent AI adoption. Through data analysis and performance reporting, you will measure productivity improvements, demonstrate return on investment, and identify opportunities for further optimization. Working closely with technical leaders and cross-functional stakeholders, you will play a key role in transforming software development practices while protecting sensitive patient information.

As an AI Enablement & Governance Analyst, you will connect AI strategy with practical implementation by supporting adoption, maintaining governance standards, and measuring the impact of AI across development teams. Your responsibilities will include:

Drive AI adoption and enablement: Coordinate the rollout of AI development tools, including Claude Code, GitHub Copilot, and Cursor, across Development, QA, and Business Analysis teams.
Deliver training and support: Train and onboard employees in AI-augmented workflows, organize office hours, manage certification initiatives, and facilitate internal knowledge-sharing forums.
Maintain AI documentation: Own and update the AI best-practice wiki, training resources, and agent registry to ensure teams have access to consistent guidance.
Manage AI governance: Maintain the prompt library governance process, establish quality gates, and review templates before they are approved for broader use.
Support compliance and risk management: Conduct reviews of AI tool usage involving HIPAA and Protected Health Information (PHI), coordinate with Information Security on data-flow approvals, and support risk sign-offs.
Maintain governance records: Keep the approved-tools list and AI risk register up to date, while supporting model-selection and Business Associate Agreement (BAA) verification processes.
Track AI adoption and performance: Define and monitor key indicators such as AI velocity, code-generation percentage, defect-rate changes, time-to-merge, and story points per sprint.
Prepare performance reports: Produce monthly adoption reports and quarterly executive ROI dashboards for senior technology and finance leadership.
Identify improvement opportunities: Analyze adoption gaps, recommend targeted interventions, and communicate findings to the AI Engineering and Enablement Lead.

Requirements

~2 min read

The ideal candidate combines analytical expertise, technical communication skills, and practical experience driving technology adoption and organizational change. The following qualifications are required:

At least 3 years of experience in a technical analyst, program enablement, developer experience, or related role.
Strong data analysis and dashboarding capabilities, with the ability to translate metrics into actionable insights.
Excellent technical writing and documentation skills.
Demonstrated experience in change management, employee training, and technology enablement.
Working knowledge of AI tooling ecosystems, including Claude, Gemini, and AI coding assistants, with the ability to teach and support their practical use.
Understanding of HIPAA, PHI, SOC 2, or comparable privacy and compliance requirements.
Strong cross-functional coordination and stakeholder communication skills.
Ability to manage multiple initiatives, establish clear processes, and encourage adoption across technical teams.

The following qualifications would be considered an advantage:

Experience in healthcare technology or the life sciences industry.
Previous involvement in large-scale AI adoption, governance, or developer-tooling implementation.
Familiarity with Jira and Confluence for project coordination and documentation.
Experience with business intelligence and analytics tools such as Looker, Tableau, or BigQuery.
Exposure to AI platforms and tools such as Claude, Gemini Enterprise, Einstein, Claude Code, GitHub Copilot, and Cursor.
Familiarity with Notion and other knowledge-management platforms.