AI Enablement & Governance Analyst

AItoolnavio; India; Hybrid; INR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Exposure to enterprise AI governance

Cross-functional collaboration

Professional development opportunities

Job summary

Partner company seeks an AI Enablement & Governance Analyst in India to accelerate AI-enabled development practices within a healthcare technology organization. You will drive adoption of AI tools, coordinate training, maintain governance resources, and ensure compliant, secure usage across engineering, QA, and business analysis teams.

You will monitor AI velocity, code-generation metrics, and ROI, producing monthly adoption reports and quarterly dashboards for technology and finance leadership.

Qualifications

• Three+ years of experience in a technical analyst, program enablement, 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 and employee training.

Responsibilities

• Drive AI adoption and enablement: coordinate rollout of AI development tools across Development, QA, and Business Analysis teams.
• Deliver training and support: onboard employees in AI-augmented workflows and organize office hours.
• Maintain AI documentation: update the AI best-practice wiki, training resources, and agent registry.

Skills

Data analysis

Dashboarding

Technical writing

Change management

Stakeholder communication

AI tooling knowledge

Tools

Jira

Confluence

Looker

Tableau

BigQuery

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Enablement & Governance Analyst based in India.

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.

Accountabilities

• 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

• 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.

Benefits

• Opportunity to contribute to AI transformation initiatives within healthcare and life sciences technology.

• Exposure to modern AI development tools and enterprise AI governance practices.

• Cross-functional collaboration with engineering, QA, business analysis, information security, and executive teams.

• Opportunity to shape AI adoption standards, training programs, and performance measurement frameworks.

• Meaningful contribution to responsible AI practices supporting healthcare technology and patient-focused services.

• Inclusive work environment that values professional development, collaboration, innovation, and diversity.