About the Role :

To lead the independent Line 2 oversight of artificial intelligence risk. The role owns the AI Risk Management Framework and Policy and the second line's assessment methodology, forms independent risk views on AI use cases, and provides credible challenge to Line 1 on AI lifecycle controls.

Key Responsibilities

Conduct independent risk assessments of AI use cases and AI applications across data, model, deployment, operational and cyber risk domains.
Review and challenge Line 1 AI risk assessments, materiality ratings, control design and remediation plans, and provide an independent view on risk adequacy.
Assess AI-specific risks including model behaviour and drift, human oversight, transparency, third-party AI solutions, and AI-related cyber threats.
Own and maintain the AI Risk Management Framework and Policy, ensuring alignment with evolving AI adoption and regulatory requirements.
Define AI risk assessment methodology, risk tiering, materiality criteria, and control expectations.
Oversee AI inventory governance and validate the completeness and accuracy of AI records maintained by Line 1.
Partner with business units and SMEs to embed AI governance requirements into operational processes.
Provide advisory support on AI risk, governance, and policy implementation.
Develop AI risk metrics, KRIs, thresholds, and independent risk reporting for senior management, risk committees, and the Board.
Monitor emerging AI risks and regulatory developments, including MAS AI Risk Management Guidelines and FEAT Principles.
Serve as the local AI risk subject matter expert and key liaison with Group and relevant stakeholders.

Requirements

Degree in Engineering, Computer Science, Information Systems, Data Science or related discipline preferred.
At least 6 years across technology, technology risk, cyber security, data or model risk, operational risk or audit.
Working knowledge of a complex banking technology environment, and the ability to find one's way around it without extended orientation.
Experience in independent risk assessment and in challenging technical stakeholders constructively.
Experience implementing AI governance arrangements — AI inventories, use case intake and approval, risk tiering, or lifecycle controls — would be an advantage.
Exposure to AI, machine learning, model risk or data governance. Depth in AI can be built on the job; grounding in technology risk and the banking environment matters more on arrival.

*Only shortlisted candidates will be notified.

Manager, Technology Risk Management (AI Risk & Governance)