Location: Chennai, Hyderabad, Kochi, Bangalore
- Define AI governance framework covering AI inventory, ownership, business purpose, risk classification, approved data access, permitted tools, oversight level, lifecycle status, recertification, and retirement.
- Establish governance workflows for AI intake, design review, security/privacy assessment, risk review, testing/evaluation, approval, deployment, monitoring, recertification, change control, and retirement.
- Define human oversight controls for high-risk actions affecting access controls, certified metrics, semantic definitions, privacy classifications, data quality rules, compliance evidence, production cutover, and architecture exceptions.
