ABOUT:
Makes AI systems trustworthy and compliant — governance frameworks, model risk assessment, and regulatory implementation that keep delivery out of legal and reputational trouble.
KEY RESPONSIBILITIES
Design and implement AI governance frameworks and policy for client engagements
Conduct model risk assessments and responsible-AI reviews before production go-live
Own AI regulatory implementation — mapping engagement requirements to relevant regulation (EU AI Act, sector rules)
Design and run AI red-teaming exercises for high-risk systems
Own AI testing & evaluation standards from a governance/ethics lens (bias, fairness, explainability, AI ethics)
Advise practice leads and Architects on governance risk during solution design, not just at the end
Facilitate cross-functional governance reviews across legal, technical, and business stakeholders
Be the voice that slows down a launch when risk warrants it, under commercial pressure
Train delivery teams on responsible-AI practices
REQUIREMENTS & SKILLS
6–12+ yrs in AI governance, model risk, compliance,
or responsible-AI roles
Working knowledge of AI regulation (EU AI Act, NIST AI RMF, sector-specific frameworks) and how to operationalize it
Technical enough to critically assess a model card or evaluation report, not just check a box
Familiarity with bias/fairness testing methodologies and explainability tooling
Familiar with platform-native AI safety/governance tooling — Microsoft Azure AI Content Safety, AWS Bedrock Guardrails, and Google Vertex AI safety filters; open-source evaluation tooling (Giskard, DeepEval) a positive-to-have
Experience designing red-team protocols for AI systems
Strong written policy/framework authorship — produces documents legal and technical teams both trust
Comfortable being the voice that slows down a launch when risk warrants it, under commercial pressure
Facilitates cross-functional governance reviews across legal, technical, and business stakeholders
Diplomatic but firm — holds the li
📌 AI Governance (India)
🏢 Systems
📍 India