AI governance SME friday interviews

Capgemini; Hyderabad, Pune District, Bengaluru; Vor Ort; INR 3.000.000 - 6.000.000; Vollzeit

Zusammenfassung

Capgemini is seeking an experienced AI governance professional to own the governance framework, risk tiering and model inventory across products in Hyderabad. You will operationalise EU AI Act, NIST RMF, and ISO 42001 into practical engineering controls and ensure responsible AI practices are built into product development.

The role requires translating complex regulations into actionable controls, guiding data provenance, PII handling and retention policies while overseeing evaluation,

Qualifikationen

• 8+ years in risk, compliance, audit or data governance with AI/ML focus.
• Knowledge of EU AI Act, GDPR, NIST AI RMF and ISO 42001.
• Ability to translate regulations into actionable controls.
• Experience with third-party AI risk assessments.

Aufgaben

• Own AI governance framework: intake, risk tiering, gates, inventory.
• Operationalise EU AI Act, NIST RMF, ISO 42001 into practical controls.
• Define data provenance, PII handling, retention policies.
• Stand up evaluation, red-teaming and bias testing by risk tier.
• Run AI review board and maintain audit-ready documentation and model cards.
• Advise product and legal on acceptable-use, transparency and human-oversight design.

Kenntnisse

AI risk governance

Regulatory frameworks

Controls translation

Tools

Model evaluation tools

Bias testing methods

Jobbeschreibung

Requirements

• 8+ years in risk, compliance, audit or data governance, with 2+ years focused on AI/ML
• Working knowledge of EU AI Act, GDPR, NIST AI RMF and ISO/IEC 42001
• Enough technical fluency to challenge model evaluation and monitoring claims credibly
• Track record turning regulation into controls engineers will actually adopt
• Experience with third-party/vendor AI risk assessment and contractual safeguards
• Certification such as CIPP/E, CISA or ISO 42001 lead auditor is a plus

Responsibilities

• Own the AI governance framework: intake, risk tiering, approval gates and model inventory
• Operationalise the EU AI Act, NIST AI RMF and ISO/IEC 42001 into practical engineering controls
• Define policy for data provenance, PII handling, retention and third-party model use
• Stand up evaluation, red-teaming and bias/fairness testing requirements per risk tier
• Run the AI review board and maintain audit-ready documentation and model cards
• Advise product and legal teams on acceptable-use, transparency and human-oversight design