Vice President, AI Risk Review, Risk Management Department

Date:  Jan 5, 2026
Location: 

Singapore

Office Location:  Capital Square, Singapore
  • Review Artificial Intelligence (“AI”)/Machine Learning (“ML”) use cases (including agentic AI) to ensure compliance with Singapore/APAC regulations and internal bank policies.
  • Design and operate frameworks for AI use case review, focusing on regulatory, ethical, and governance requirements.
  • Lead and support operational transformation initiatives leveraging AI, collaborating with business and technology teams to identify, design, and implement AI-enabled process improvements.
  • Provide practical guidance to business and technology stakeholders on both AI risk management and AI-driven transformation opportunities.

Job Responsibilities

AI Use Case Review

  • Conduct independent reviews of AI/ML use cases, verifying compliance with various external/internal rules, such as Singapore’s PDPA guidance, prosed MAS AI risk management guideline, and internal bank policies, including ones for Model Governance.
  • Review documentation and evidence for each AI use case, including purpose, data sourcing and privacy, model design, fairness and explainability, human-in-the-loop controls, and security measures.
  • Review agentic AI architectures for role-based access, policy-as-code, immutable decision logging, observability, and fallback/kill-switch mechanisms.
  • Advise first line teams on regulatory and policy requirements for AI use cases, providing actionable recommendations for remediation or improvement.
  • Prepare clear review reports and present findings to senior management and relevant committees.
  • Monitor regulatory developments and update review frameworks as needed.

AI-driven Operational Transformation

  • Identify opportunities for operational transformation leveraging AI, in collaboration with business and technology teams.
  • Lead or support the design and implementation of AI-enabled process improvements, automation, and digital transformation initiatives.
  • Evaluate risk and control implications of AI-driven transformation projects, ensuring alignment with regulatory and internal governance requirements.
  • Promote responsible AI adoption and innovation within the organization.
  • Share best practices and lessons learned from AI transformation projects across APAC branches.

Job Requirements

  • Bachelor’s degree in Computer Science, Data Science, Engineering, Information Systems, or related field; advanced degree or recognized certifications are advantageous.
  • 5–10 years of experience in AI/ML use case review, model risk management, data/AI governance, technology risk, or operational transformation within financial services.
  • Demonstrated knowledge of Singapore AI governance landscape (e.g., PDPC, MAS expectations, Model Governance) and familiarity with global frameworks, e.g., EU AI Act (preferable).
  • Experience leading or supporting AI-driven operational transformation projects, including process redesign, automation, or digitalization.
  • Strong stakeholder management and communication skills; able to challenge constructively and provide practical, risk-based recommendations.
  • Proactive self-starter with strong teamwork abilities and stakeholder management skills.
  • Able to multi-task under tight timelines.
  • Native-level English proficiency required; culturally sensitive and able to work in a diverse APAC environment.

Core Skills Set

Working knowledge and/or experience in the following areas:

  • AI Governance & Review: designing and operating review frameworks for AI use cases.
  • Data Governance & Privacy: consent/legitimate basis assessment, data lineage/quality, anonymisation, and PDPA compliance.
  • Model Risk & Validation: fairness/bias testing, explainability, robustness, drift monitoring, documentation and traceability.
  • Security & Resilience: secure MLOps, access control, secret management, supply-chain risk, adversarial testing.
  • Agentic AI Guardrails: least-privilege tool use, policy-as-code, immutable decision logs, human-in-the-loop and safe fallback.
  • AI Transformation: process redesign, automation, digitalization, and change management.
  • Regulatory Intelligence: horizon scanning and translating regulatory/standards into bank policies and review criteria.