AI Cybersecurity Governance (m/f/d)
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Key skills for this role
About the Role
Halian seeks an AI Governance & Model Risk Manager for a banking client in Abu Dhabi. The role designs and enforces AI governance frameworks aligned with EU AI Act and CBUAE principles, manages model risk for generative AI, and conducts cyber risk assessments for AI/ML infrastructure.
Key Skills for This Role
Responsibilities
- Develop, implement, and maintain enterprise wide AI governance frameworks in alignment with EU AI Act and CBUAE AI principles
- Design and implement model risk management frameworks tailored to generative AI and advanced ML models
- Conduct cybersecurity risk assessments for AI/ML platforms, including cloud based AI environments
- Develop risk dashboards, KPIs, and KRIs for AI governance and model risks
- Collaborate with Risk, Compliance, Data, Technology, and Business teams to embed AI governance practices
- Provide advisory support on AI use cases, ensuring risk by design principles
Requirements
- Bachelor’s or Master’s degree in Data Science, Computer Science, AI/ML, Risk Management, Finance, or related field
- 6–10+ years of experience in Model Risk Management / Technology Risk / AI Governance in banking or financial services
- Hands on experience with Generative AI models and ML lifecycle
- Strong knowledge of AI/ML concepts, LLMs, and generative AI risks
- Familiarity with cloud platforms (Azure, AWS, GCP) AI services
- Understanding of data governance, privacy, and ethical AI principles
Full Job Posting
Role Overview
- The AI Governance & Model Risk Manager will be responsible for designing, implementing, and enforcing AI governance frameworks aligned with EU AI Act and CBUAE AI principles. The role focuses on ensuring robust model risk management for generative AI and conducting cyber risk assessments for AI/ML i
Key Responsibilities
- AI Governance & Regulatory Compliance: Develop, implement, and maintain enterprise wide AI governance frameworks in alignment with EU AI Act requirements and CBUAE AI principles.
- Establish policies, standards, and procedures for responsible AI usage across business units.
- Ensure proper classification, documentation, and lifecycle management of AI systems (including high risk AI use cases).
- Act as the central point of contact for regulatory engagement related to AI governance.
- Monitor regulatory developments and ensure timely updates to governance frameworks.
- Model Risk Management (MRM) – Generative AI: Design and implement model risk management frameworks tailored to generative AI and advanced ML models.
- Define model validation, approval, monitoring, and periodic review processes.
- Establish controls around model explainability, bias/fairness testing, data quality, model drift, etc.
- Partner with Data Science and Technology teams to ensure risk aware model development and deployment.
- Maintain model inventory and risk classification aligned with internal and regulatory expectations.
- Cyber Risk & AI Infrastructure Security: Conduct cybersecurity risk assessments for AI/ML platforms, including cloud based AI environments.
- Identify vulnerabilities in AI lifecycle components including data pipelines, training environments, and inference endpoints.
Qualifications & Experience
- Education: Bachelor’s or Master’s degree in Data Science, Computer Science, AI/ML, Risk Management, Finance, or related field.
- Experience: 6–10+ years of experience in Model Risk Management / Technology Risk / AI Governance in banking or financial services (mandatory or highly preferred).
- Hands on experience with Generative AI models and ML lifecycle.
- Regulatory frameworks (EU AI Act, CBUAE guidelines, or similar).
- Technical & Functional Skills: Strong knowledge of AI/ML concepts, LLMs, and generative AI risks.
- Model validation and risk frameworks (SR 11 7 or equivalent).
- Familiarity with cloud platforms (Azure, AWS, GCP) AI services.
- Cybersecurity principles related to AI systems.
- Understanding of data governance, privacy, and ethical AI principles.
- Soft Skills: Strong analytical and risk assessment capabilities.
- Excellent stakeholder management and communication skills.
- Ability to translate regulatory requirements into practical frameworks.
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