Lead development and refinement of the banks AI risk framework; apply frameworks to use cases; review higher-risk AI applications; liaise with business, technology, and control owners; track remediation and emerging risk themes; prepare governance materials and monitor regulatory developments.
Business Function
Risk Management Group (RMG) is responsible for the development and maintenance of risk management and internal control frameworks. It provides independent review and challenge to ensure appropriate balance in risk/return decisions, and monitors key risk issues across the Bank.
The role sits within the Data & AI Risk (DAR) team and is focused on the development and ongoing refinement of the Group’s AI risk framework, ensuring it is practical, aligned to regulatory expectations, and applied consistently across the organisation.
Responsibilities:
- Support development and refinement of AI risk policy, taxonomy, and control expectations
- Apply AI risk frameworks to specific use cases and scenarios
- Support review of higher-risk AI use cases and provide structured risk input
- Work with business, technology, and platform teams to understand use cases and identify key risks
- Assist in translating policy into clear, practical requirements and guidance
- Work with standard and control owners to support alignment to risk expectations
- Track and follow up on issues, gaps, and remediation actions
- Collate and analyse emerging risk themes from use cases and incidents
- Support preparation of materials for governance forums and senior management engagement
- Keep across industry developments and regulatory updates, providing first-cut analysis
- Contribute to improving consistency in how AI risks are identified and articulated
Requirements:
- Experience in risk management, with grounding in at least one established domain (e.g. model, cyber, data risk)
- Exposure to AI / advanced analytics / technology risk preferred but not mandatory
- Ability to apply frameworks in practice, not just understand them conceptually
- Good analytical skills and ability to structure risk issues clearly
- Comfortable working across multiple teams and evolving subject matter
- Strong analytical and problem-solving skills, with the ability to assess risks and identify practical solutions
- Excellent communication skills, with the ability to engage effectively with both technical and non-technical stakeholders
- Bachelor’s degree in a relevant field (e.g. Accounting, Banking, Computer Science, Engineering, Mathematics, Statistics); relevant certifications (e.g. CRISC, CISM) are advantageous
Location:
DBS Asia CentralJob:
ComplianceSchedule:
RegularEmployee Status:
Full timeDBS Bank Ltd Singapore Office
Similar Jobs
Fintech • Information Technology • Software • Financial Services
Lead development and maintenance of a bank-wide Data and AI risk management framework. Assess new initiatives, conduct risk reviews, embed controls across data and AI lifecycles, monitor data quality and KRIs, advise business units, align with regulations and industry best practices, and report risks and mitigation strategies to senior management.
Top Skills:
Ai GovernanceApplied Machine LearningData GovernanceModel Risk Management
.jpeg)
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Lead a team to design and implement CMOS device solutions for NAND products, improving yield and reliability while managing cross-department collaborations and fostering team development.
Top Skills:
AICmosNand
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Lead package reliability, qualification, and failure analysis across NPI and HVM. Drive test methodology, risk assessment, DFR/DFM integration, cross-functional collaboration, team development, and use of data/AI to improve reliability and enable product ramps across mobile, automotive, data center, and AI/HPC segments.
Top Skills:
8D Root Cause AnalysisAec-QAi-Enabled ToolsBoard-Level ReliabilityCross-SectioningDesign For Manufacturability (Dfm)Design For Reliability (Dfr)Digital Quality SystemsDramEdxFailure AnalysisHastHbmHybrid BondingJedecMslNandOsatsPreconditioningPredictive Reliability AnalyticsSamSemSystem-In-PackageTemperature CyclingX-Ray
What you need to know about the Singapore Tech Scene
The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.
