Senior Officer, AI Governance (40000070)

• Support the development and implementation of the AI Governance framework within the organization:
• Define policies, standards, and procedures for the development, deployment, and usage of AI systems.
• Ensure AI systems comply with internal policies, regulatory requirements, data privacy, and security standards.
• Collaborate with cross-functional teams:
• Work closely with Data Engineers, Data Scientists, IT teams to understand system architecture, data flows, and AI models.
• Partner with Risk, Compliance, and Audit teams to assess and manage risks related to AI systems.
• Conduct AI risk assessment and monitoring:
• Identify risks related to data quality, bias, model performance, privacy, and security.
• Propose and implement controls to mitigate risks and ensure ongoing monitoring of AI models.
• Support audit and compliance activities:
• Prepare documentation and evidence for internal and external audits.
• Track and address audit findings related to AI, data, and technology risks.
• Contribute to AI lifecycle governance:
• Support governance across the AI lifecycle (development, validation, deployment, monitoring).
• Ensure proper documentation, model versioning, and monitoring processes are in place.
• Stay updated on AI governance trends and best practices:
• Monitor emerging regulations, standards, and frameworks related to Responsible AI and AI Ethics.
• Recommend improvements to governance frameworks and practices.

Experience & Background

• 3–5 years of experience in one or more of the following areas:
• Information Systems / IT / Data Engineering
• IT Risk / IT Audit (preferably in banking or financial services)
• Data Governance / Data Management
• Strong understanding of:
• System architecture, data flows, and enterprise applications
• Data platforms, databases, and data processing concepts
• Information Security, Data Privacy, and Risk Management principles

Skills & Competencies

• Strong analytical and system thinking to understand complex technology environments.
• Ability to work effectively with cross-functional stakeholders (Data, IT, Risk, Business).
• Capable of translating technical concepts into policies, standards, and procedures.
• Strong problem-solving and risk assessment skills.

Additional Requirements

• Bachelor’s degree in Information Systems, Computer Science, Data Science, Risk Management, or related fields.
• Experience or exposure to AI / Machine Learning is a strong advantage.
• Familiarity with AI Governance, Model Risk Management, or Responsible AI frameworks is a plus.
• Good English communication skills (reading technical documents and basic communication).