New opportunity

AI Governance (GDMO) (ED/VP)

OCBC Bank · Singapore

About this role

Role Purpose: As part of the Group Data Management Office (GDMO), you will play a pivotal role in developing model risk and AI governance standards and controls across the Group. This position focuses on ensuring AI solutions are used responsibly and in compliance with regulatory and internal requirements, while supporting the optimization of risk assessment processes through Agentic AI. Responsibilities: Lead governance reviews and assessments of AI use cases, including risk assessments, inventory management, and documentation reviews. Collaborate with model developers, technology teams, and business users to implement governance requirements, controls, and guardrails throughout the AI lifecycle. Coordinate with independent validators, auditors, compliance teams, and regulators to track findings and support governance actions. Monitor emerging AI regulations and industry best practices to enhance control standards. Drive the operationalization of the Group's model and AI inventory. Provide secretariat support to the AI Council and AI Governance Working Group. Qualifications: 8-10 years of relevant experience in AI governance, model risk management, or a related field. Strong understanding of AI, Machine Learning, Generative AI, and Agentic AI concepts. Experience in implementing AI or Gen AI guardrails is preferred. Familiarity with AI and data-related governance frameworks and regulatory requirements is advantageous. Proficiency in data analytics, SQL, or Python is beneficial. Strong analytical, problem-solving, and communication skills are required to engage with diverse stakeholders. Benefits: Competitive base salary, holistic flexible benefits, community initiatives, and industry-leading professional development opportunities.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

AI GovernanceModel Risk ManagementGenerative AIAgentic AIAI GuardrailsRisk AssessmentRegulatory ComplianceData AnalyticsSQLPythonStakeholder Management

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Establish AI Governance Frameworks
Develop and maintain robust standards and controls for AI and model risk management. This requires translating complex regulatory requirements into actionable guardrails that span the entire AI lifecycle, from initial development to deployment and ongoing monitoring.
Operationalize AI Inventory and Risk Assessment
Drive the systematic documentation and tracking of AI use cases across the Group. This involves managing the AI inventory and utilizing Agentic AI to streamline risk assessment processes, ensuring all models are accounted for and compliant with internal standards.
Cross-Functional Stakeholder Engagement
Act as a bridge between technical teams (model developers, IT) and risk/compliance functions. Success depends on the ability to communicate governance requirements clearly to non-technical stakeholders while ensuring technical teams understand and implement necessary guardrails.
Secretariat Support for AI Governance Bodies
Provide administrative and strategic support to the AI Council and AI Governance Working Group. This includes tracking governance actions, managing audit trails, and ensuring that leadership is informed of emerging regulatory developments and industry best practices.

Likely challenges to think through

Balancing Innovation with Risk Mitigation
The role requires supporting business innovation while maintaining strict governance. Prepare by demonstrating how you have previously implemented 'guardrails' that enable speed-to-market without compromising safety or regulatory compliance.
Managing Evolving Agentic AI Risks
Agentic AI introduces unique, dynamic risks compared to traditional models. Prepare by articulating your approach to monitoring autonomous systems and how you would design controls that adapt to the non-deterministic nature of AI agents.
Navigating Complex Regulatory Environments
As a bank, OCBC operates under stringent oversight. Prepare by showing how you stay current with global AI regulations and how you translate high-level regulatory expectations into specific, enforceable internal policies.

Practice your answers

Technical practice

Implementing Guardrails for Agentic AI

What to coverDiscuss the specific challenges of implementing guardrails for autonomous agents compared to traditional static AI models. Focus on how you would manage non-deterministic outputs, maintain human-in-the-loop oversight, and ensure compliance with internal risk frameworks.

AI Model Risk Management Lifecycle

What to coverExplain the key stages of the AI model lifecycle from development to deployment and monitoring. Detail how you would integrate governance controls and documentation requirements at each stage to ensure auditability and regulatory compliance.

Regulatory Compliance in Financial Services AI

What to coverHow do you stay updated on emerging AI regulations and translate these requirements into actionable internal control standards? Provide an example of how you would balance strict regulatory adherence with the need for business innovation.

Operationalizing AI Inventory Management

What to coverDescribe your approach to building and maintaining a comprehensive AI and model inventory. Address how you ensure data accuracy, track model lineage, and maintain audit trails for diverse AI use cases across a large organization.

Risk Assessment Methodologies for Gen AI

What to coverWhat specific risks do you prioritize when conducting a governance review for a Generative AI use case? Discuss how you evaluate potential issues like hallucination, data privacy, and bias within a banking context.

Data Analytics for Governance Monitoring

What to coverHow can SQL or Python be utilized to automate the monitoring of AI model performance or compliance metrics? Suggest ways to use these tools to identify anomalies or potential drift in production AI systems.

Behavioural practice

Managing Conflicting Stakeholder Priorities

What to coverDescribe a situation where you had to balance strict governance requirements with the urgent needs of business or technology teams. How did you communicate the risks while maintaining a collaborative relationship?

Influencing Cross-Functional Teams

What to coverProvide an example of how you successfully persuaded a non-technical stakeholder to adopt a new governance control or process. Focus on how you tailored your communication to address their specific concerns.

Handling Audit Findings and Remediation

What to coverTell me about a time you had to coordinate with auditors or regulators regarding a governance finding. How did you manage the remediation process and ensure timely closure of the action items?

Prioritizing Multiple Concurrent Governance Workstreams

What to coverIn a fast-paced environment, how do you manage competing deadlines for multiple AI governance reviews? Describe your method for organizing tasks and ensuring that no critical risk assessment is overlooked.

Sharpen your knowledge

Topics to prepare

AI and Agentic AI Governance Frameworks
Review established AI risk management frameworks (e.g., NIST AI RMF, ISO/IEC 42001) and adapt them to the specific challenges of Agentic AI, such as autonomy, non-deterministic outputs, and multi-agent system risks. This is critical for the role's responsibility in developing governance standards and controls.
Model Risk Management (MRM) in Banking
Study traditional MRM principles and how they apply to the AI lifecycle, including model validation, inventory management, and documentation requirements. This is essential for aligning AI initiatives with the bank's existing risk appetite and regulatory compliance standards.
Emerging AI Regulatory Landscape
Research current and upcoming AI regulations relevant to the financial sector in Singapore and globally. Practice mapping these regulatory requirements to internal control standards to ensure the bank remains compliant while fostering innovation.

Skills to revise

Designing AI and Gen AI Guardrails
Practice defining technical and procedural guardrails for LLM-based applications, such as input sanitization, output filtering, and human-in-the-loop verification. This directly addresses the requirement to implement controls throughout the AI lifecycle.
Stakeholder Management and Communication
Prepare to explain complex AI risks and governance requirements to non-technical business users and senior management. Develop a structured approach for tracking governance findings and coordinating with auditors and compliance teams.
Data Analytics for Governance Reporting
Use SQL or Python to analyze model inventory data or risk assessment logs. This skill is beneficial for the role's focus on operationalizing the Group's AI inventory and providing secretariat support to governance working groups.

Your preparation checklist

Map AI Governance Frameworks to Financial Regulations
Prepare a summary of how you have aligned AI development lifecycles with industry-standard frameworks like NIST AI RMF or MAS guidelines. Be ready to discuss how you balance innovation with strict regulatory compliance in a banking environment.
Develop a Case Study on AI Guardrails
Prepare a project walkthrough detailing your experience implementing guardrails for Generative AI or Agentic AI. Focus on specific technical or process-based controls you designed to mitigate risks such as hallucination, data leakage, or bias.
Draft a Strategy for Agentic AI Risk Assessment
Create a brief outline on how you would optimize the risk assessment process using Agentic AI. Explain how you would maintain human-in-the-loop oversight while leveraging automation to improve efficiency in model inventory management.
Prepare Stakeholder Management Examples
Identify specific instances where you successfully navigated conflicting priorities between technical model developers and non-technical business or compliance stakeholders. Focus on your communication style and how you achieved consensus on governance requirements.
Formulate Strategic Questions for the Interviewer
Prepare thoughtful questions regarding the current maturity of OCBC's AI inventory, the specific challenges the AI Governance Working Group is currently prioritizing, and how the team balances rapid AI adoption with the bank's risk appetite.

Availability last checked: 18 Oct 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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