AI, Data Governance & Privacy Officer I Dubai | Financial Services

Enterprise AI Governance Establish and maintain the enterprise AI Governance Framework. Define policies, standards, controls, and operating procedures for AI usage. Create governance models for: Agentic AI Generative AI Machine Learning Advanced Analytics Intelligent Automation Chair the AI Governance Committee. Define AI approval and risk assessment processes. Ensure AI initiatives align with: Regulatory requirements Ethical AI principles Security policies Business objectives Implement AI lifecycle governance across development, deployment, monitoring, and retirement. Develop controls for: Explainability Fairness Bias management Human oversight Model monitoring Prompt governance Auditability 2. Data Governance & Information Management Develop and operate the enterprise data governance framework. Establish data ownership and stewardship models. Define enterprise standards for: Data quality Metadata management Master data management Data lineage Data retention Data classification Lead enterprise data cataloguing and inventory programmes. Implement data governance tooling and controls. Develop governance measures for structured and unstructured data. Drive data quality improvement initiatives across business functions. Establish governance for enterprise data platforms, analytics environments, GenAI platforms, and data lakes. 3. Privacy & Data Protection Act as Data Protection Officer (where required by regulation). Lead compliance with: UAE PDPL DIFC Data Protection Law GDPR Other applicable regional privacy regulations Define and maintain enterprise privacy frameworks. Conduct and oversee: Data Protection Impact Assessments (DPIAs) Privacy Risk Assessments Third-party Privacy Reviews Establish Privacy by Design practices across business and technology initiatives. Manage: Data Subject Rights Requests Consent management processes Cross-border transfer assessments Breach response governance 4. AI Risk & Model Governance Define model governance standards. Establish model risk management processes. Classify AI systems based on risk and criticality. Develop controls for: Model validation Performance monitoring Drift detection Explainability Human-in-the-loop oversight Maintain an enterprise AI model inventory. Conduct periodic AI risk assessments. Ensure regulatory readiness for emerging AI regulations. 5. Regulatory Compliance & Audit Monitor evolving AI, privacy, and data regulations globally. Translate regulatory requirements into governance controls. Coordinate regulatory responses and examinations. Support Internal Audit, Risk, Compliance, and External Audit activities. Maintain evidence repositories for governance and compliance activities. Lead remediation of governance and privacy findings. 6. Vendor, Third-Party & Cloud Governance Define governance requirements for AI vendors and data processors. Review: SaaS contracts AI solution providers Data sharing arrangements Third-party processing agreements Assess external AI platforms for privacy, security, compliance, and ethical risk. Establish governance controls for third-party LLMs and foundation model providers. 7. Governance Awareness & Culture Develop enterprise-wide training programmes on: Responsible AI Data governance Data protection Information handling Build a culture of responsible innovation. Conduct executive awareness sessions and governance workshops. Develop reporting dashboards and governance KPIs.

Desired Candidate Profile

Education Bachelor's Degree in Computer Science, Information Systems, Data Science, Cybersecurity, Law, or related field. Master's Degree preferred. Experience 10+ years of experience in data governance, privacy, risk, information management, or technology governance. Minimum 5 years leading enterprise governance initiatives. Experience within insurance, financial services, banking, or regulated industries preferred. Practical experience governing: AI/ML platforms Generative AI Cloud platforms Enterprise data environments Employment Type Full-time

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