AI Governance Manager

About the role

The AI Governance Manager builds and runs the framework that lets the business adopt AI safely, responsibly and in line with regulation. You will own policy, standards and oversight across the AI lifecycle, from use case intake and risk assessment through to deployment, monitoring and retirement. You will work with data science, technology, risk, legal, compliance and the business, and report on AI risk to senior management and relevant committees.

Key responsibilities

• Design, implement and maintain the AI governance framework, policies and standards, aligned to the organisation's risk appetite and wider risk and control environment
• Run the AI use case inventory and intake process, including risk tiering, approvals and ongoing review
• Lead risk and impact assessments covering fairness, explainability, transparency, privacy, security, robustness and third-party risk
• Embed governance controls into model development, validation and deployment, including generative AI and vendor-supplied AI
• Track regulatory and industry developments and translate them into practical requirements for the business
• Define monitoring approaches and key risk indicators, and produce management information and committee reporting
• Coordinate with model risk management, data protection, information security, legal and internal audit, and support regulatory and audit engagements
• Build awareness and capability through training, guidance and day-to-day advice to product, data and engineering teams
• Manage direct reports and work with external advisers where needed

Required profile

• Minimum eight years of experience in AI governance, model risk, data governance, technology risk, compliance or a related field, with at least three years directly on AI or machine learning governance
• Degree in a relevant discipline such as computer science, data science, law, risk or engineering
• Proven ability to turn regulation and principles into practical controls that technical teams will follow
• Excellent stakeholder management and communication, including with senior management and non-technical audiences

Required skills

• Working knowledge of the AI lifecycle and how machine learning and generative AI systems are built, tested and deployed
• Familiarity with frameworks such as the NIST AI Risk Management Framework, ISO/IEC 42001, the EU AI Act, the Singapore Model AI Governance Framework and MAS guidance on AI risk management
• Familiarity with data protection requirements, including the PDPA
• Desirable: experience in a regulated financial services environment; professional certification such as AIGP, CISA, CRISC or ISO/IEC 42001 lead implementer; hands-on exposure to model validation or responsible AI tooling