Senior Manager - AI Security Product Owner

Client of Forsyth Barnes; Abu Dhabi; On-site; AED 900,000 - 1,500,000; Full time

Benefits offered by this job

Senior leadership role

Abu Dhabi location

Cross-functional exposure

Competitive reward package

Job summary

Client of Forsyth Barnes in Abu Dhabi seeks a Senior Manager - AI Security Product Owner to define and lead the product strategy for protecting AI/ML across a major banking environment. You will drive a security vision, roadmap, governance, and lifecycle controls spanning cloud, on-prem, and hybrid models.

Role requires senior cross-functional leadership across cybersecurity, data, risk, compliance, architecture, and external providers; translating regulatory expectations into practical controls

Qualifications

• Extensive experience in cybersecurity, AI security, or ML governance.
• Proven ability to translate AI threats into practical controls.
• Experience with risk, compliance, and policy in regulated industries.
• Understanding of MLOps, LLMOps, DevSecOps and cloud security.

Responsibilities

• Set strategic direction and roadmaps for AI security products and capabilities
• Translate regulatory obligations into a prioritised AI security backlog
• Define security-by-design and privacy-by-design requirements for AI lifecycles
• Establish governance gates for AI use-cases, data, models and deployment
• Lead security integration across MLOps, LLMOps, DevSecOps, cloud and on-premises
• Coordinate threat modelling, vulnerability management and control validation
• Assess AI threats including prompt injection and data poisoning
• Align practices with UAE requirements and GDPR where relevant
• Maintain risk registers, governance documentation and audit evidence
• Direct third-party assessments for AI vendors and platforms
• Define monitoring for model behaviour, data flows and security controls
• Prepare for AI-related incidents with playbooks and remediation tracking
• Measure outcomes via control coverage, risk reduction and audit readiness

Skills

AI security

Security product ownership

Risk management

Regulatory compliance

Cloud security

Communication to executives

Education

CISSP

CISM

CCSP

CRISC

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
• 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