Senior Manager - AI Security Product Owner (Ref: 197825)

• about the role About Us Operating from Abu Dhabi since 1985, our client provides personal and business banking services across retail banking, wealth management, commercial banking, corporate finance, investment banking, and cash management. Its diverse financial services platform supports customers and markets through a complex technology environment where resilient controls, responsible innovation, and secure use of artificial intelligence are business priorities. As AI adoption develops across banking operations and customer-facing services, this organisation is strengthening the governance and protection of the models, data, platforms, and processes that enable those capabilities. The role contributes to a regulated financial institution with broad operational reach and a clear focus on building trustworthy, controlled, and sustainable AI services. Job Description The Senior Manager - AI Security Product Owner will define and lead the product strategy for protecting artificial intelligence and machine learning capabilities across a major banking environment. The role owns the security product vision, roadmap, prioritisation, and lifecycle, ensuring that AI initiatives can progress at pace without compromising confidentiality, resilience, privacy, regulatory compliance, or customer trust. Success will require close direction of cross-functional delivery spanning cybersecurity, engineering, data, product, risk, compliance, architecture, operations, and external providers. You will translate emerging AI threats and regulatory expectations into practical controls, embed security throughout model and application lifecycles, and establish measurable governance across cloud, on-premises, and hybrid environments. From secure MLOps and LLMOps pipelines to operational monitoring and incident management, the position will create a consistent control framework for AI adoption. You will provide senior-level oversight of risk decisions, evidence-based assurance, remediation activity, and continuous improvement, helping this organisation scale useful AI capabilities while maintaining a disciplined security posture. Key Responsibilities • Set the strategic direction, investment priorities, delivery roadmap, and operating model for AI security products and capabilities. • Convert business objectives, threat intelligence, risk findings, and regulatory obligations into a prioritised AI security backlog. • Define security-by-design and privacy-by-design requirements for AI models, applications, data pipelines, platforms, and supporting services. • Establish governance gates covering AI use-case approval, data suitability, model risk, testing, deployment, change control, and retirement. • Lead security control integration across MLOps, LLMOps, DevSecOps, cloud, on-premises, and hybrid technology environments. • Coordinate threat modelling, architecture reviews, vulnerability management, penetration testing, and control validation for AI solutions. • Assess exposure to prompt injection, data poisoning, model extraction, insecure output handling, adversarial manipulation, and other relevant AI threats. • Partner with risk and compliance teams to align practices with applicable UAE requirements, GDPR where relevant, internal policy, and recognised frameworks. • Maintain AI security risk registers, control libraries, governance documentation, executive reporting, and audit evidence. • Direct third-party assessments for AI vendors, foundation models, platforms, data services, and outsourced operational components. • Define monitoring requirements for model behaviour, access, data flows, logging, anomalous activity, misuse, and control performance. • Support preparedness for AI-related incidents, including playbooks, escalation routes, forensic requirements, root-cause analysis, and remediation tracking. • Measure product outcomes through meaningful indicators such as control coverage, risk reduction, remediation velocity, adoption quality, and audit readiness. • Facilitate decisions among senior stakeholders when security, delivery speed, commercial value, and risk appetite require careful trade-offs. Requirements • Bring substantial senior experience across cybersecurity, AI security, machine learning governance, technology risk, product ownership, or closely related disciplines. • Show a strong working understanding of AI and machine learning architectures, model lifecycles, data protection, application security, and emerging AI attack techniques. • Demonstrate experience defining and delivering security products, platforms, controls, or governance capabilities in complex enterprise environments. • Understand secure MLOps, LLMOps, DevSecOps, cloud security, identity and access management, secrets protection, monitoring, and secure software delivery. • Apply practical knowledge of cybersecurity and governance frameworks such as NIST CSF, NIST AI RMF, ISO 27001, ISO 42001, SOC 2, and relevant privacy requirements. • Be comfortable interpreting regulatory expectations and converting them into policies, control objectives, implementation standards, and measurable assurance activities. • Have experience managing product roadmaps, agile delivery, prioritisation, budgets, dependencies, vendors, and outcomes across multiple stakeholder groups. • Communicate complex technical and risk matters clearly to executive leaders, engineers, product teams, auditors, regulators, and business owners. • Use structured judgement to evaluate residual risk, document exceptions, challenge assumptions, and drive accountable remediation. • Bring experience within banking, financial services, or another highly regulated industry, with a clear appreciation of confidentiality, resilience, and customer impact. • Hold or be working towards a relevant qualification such as CISSP, CISM, CRISC, CCSP, or an equivalent security and risk certification. • Additional certification in cloud security, AI governance, AI security, privacy, or agile product ownership would be advantageous. Benefits • Take ownership of a high-visibility AI security portfolio with direct relevance to the future of regulated banking. • Influence enterprise-wide standards for responsible AI adoption across diverse banking businesses and technology environments. • Work at the intersection of product strategy, cybersecurity, data, engineering, risk, compliance, and emerging technology. • Engage with senior decision-makers and shape governance practices that support secure innovation rather than relying solely on reactive controls. • Build a distinctive leadership profile in a rapidly developing discipline with growing strategic importance across financial services. • Access opportunities to deepen expertise through relevant certifications, industry learning, and exposure to evolving AI security practices. • Operate from Abu Dhabi within an established financial institution offering broad business scope and meaningful organisational visibility. • Receive a competitive senior-level reward package and access to the resources required to deliver a complex, enterprise-wide mandate. Other The position is based in Abu Dhabi and requires the judgement to balance innovation with the control standards expected of a financial institution. Candidates should be able to demonstrate outcomes from buildin

Bring substantial senior experience across cybersecurity, AI security, machine learning governance, technology risk, product ownership, or closely related disciplines. Show a strong working understanding of AI and machine learning architectures, model lifecycles, data protection, application security, and emerging AI attack techniques. Demonstrate experience defining and delivering security products, platforms, controls, or governance capabilities in complex enterprise environments. Understand secure MLOps, LLMOps, DevSecOps, cloud security, identity and access management, secrets protection, monitoring, and secure software delivery. Apply practical knowledge of cybersecurity and governance frameworks such as NIST CSF, NIST AI RMF, ISO 27001, ISO 42001, SOC 2, and relevant privacy requirements. Be comfortable interpreting regulatory expectations and converting them into policies, control objectives, implementation standards, and measurable assurance activities. Have experience managing product roadmaps, agile delivery, prioritisation, budgets, dependencies, vendors, and outcomes across multiple stakeholder groups. Communicate complex technical and risk matters clearly to executive leaders, engineers, product teams, auditors, regulators, and business owners. Use structured judgement to evaluate residual risk, document exceptions, challenge assumptions, and drive accountable remediation. Bring experience within banking, financial services, or another highly regulated industry, with a clear appreciation of confidentiality, resilience, and customer impact. Hold or be working towards a relevant qualification such as CISSP, CISM, CRISC, CCSP, or an equivalent security and risk certification. Additional certification in cloud security, AI governance, AI security, privacy, or agile product ownership would be advantageous.

Set the strategic direction, investment priorities, delivery roadmap, and operating model for AI security products and capabilities. Convert business objectives, threat intelligence, risk findings, and regulatory obligations into a prioritised AI security backlog. Define security-by-design and privacy-by-design requirements for AI models, applications, data pipelines, platforms, and supporting services. Establish governance gates covering AI use-case approval, data suitability, model risk, testing, deployment, change control, and retirement. Lead security control integration across MLOps, LLMOps, DevSecOps, cloud, on-premises, and hybrid technology environments. Coordinate threat modelling, architecture reviews, vulnerability management, penetration testing, and control validation for AI solutions. Assess exposure to prompt injection, data poisoning, model extraction, insecure output handling, adversarial manipulation, and other relevant AI threats. Partner with risk and compliance teams to align practices with applicable UAE requirements, GDPR where relevant, internal policy, and recognised frameworks. Maintain AI security risk registers, control libraries, governance documentation, executive reporting, and audit evidence. Direct third-party assessments for AI vendors, foundation models, platforms, data services, and outsourced operational components. Define monitoring requirements for model behaviour, access, data flows, logging, anomalous activity, misuse, and control performance. Support preparedness for AI-related incidents, including playbooks, escalation routes, forensic requirements, root-cause analysis, and remediation tracking. Measure product outcomes through meaningful indicators such as control coverage, risk reduction, remediation velocity, adoption quality, and audit readiness. Facilitate decisions among senior stakeholders when security, delivery speed, commercial value, and risk appetite require careful trade-offs.