Senior Manager – AI Security Product Owner

Job Description Title: Senior Manager – AI Security Product Owner Role Purpose The Senior Manager – AI Security Product Owner is responsible for defining, driving, and overseeing the strategy, design, and delivery of secure AI/ML products and platforms. The role ensures that AI solutions are developed and deployed in alignment with cybersecurity standards, regulatory requirements, and enterprise risk frameworks, while enabling innovation and business value realization. Key Accountabilities AI Security Product Strategy & Ownership • Define and own the end-to-end product vision, roadmap, and lifecycle for AI security solutions. • Collaborate with business, technology, and cybersecurity teams to identify secure AI use cases and prioritize delivery. • Embed security-by-design and privacy-by-design principles into AI/ML product development. AI/ML Security & Risk Governance • Establish and enforce AI security controls covering model development, deployment, and monitoring. • Perform AI risk assessments addressing data privacy, model bias, explainability, and regulatory compliance. • Ensure alignment with frameworks such as NIST AI RMF, ISO 42001, and enterprise cybersecurity standards. Secure Product Delivery & Integration • Lead secure AI product delivery across cloud, on-prem, and hybrid environments. • Integrate security controls into MLOps/LLMOps pipelines, ensuring continuous control validation. • Drive secure SDLC practices including threat modeling, vulnerability management, and secure deployment. Stakeholder & Vendor Management • Act as the key interface between Product, Engineering, Cybersecurity, Risk, Compliance, and external vendors. • Manage third-party AI solution risk assessments and ensure adherence to security and contractual obligations. Governance, Compliance & Audit • Ensure compliance with regulatory requirements (e.g., UAE regulations, GDPR, internal policies). • Support internal and external audits, ensuring timely closure of findings and remediation tracking. • Maintain AI risk registers, documentation, and governance reporting. Monitoring, Incident Response & Continuous Improvement • Define monitoring frameworks for AI systems including logging, anomaly detection, and abuse prevention. • Lead AI-related incident response and root cause analysis. • Continuously enhance AI security posture based on emerging threats (e.g., OWASP LLM risks, adversarial AI). Knowledge, Skills & Experience • 12+ years of experience in Cybersecurity, AI/ML Security, Product Ownership, or related domains. • Strong expertise in: • AI/ML security, governance, and risk management • Cloud security (AWS, Azure, GCP) and DevSecOps • GRC frameworks (ISO 27001, NIST, SOC2, GDPR) • Experience in AI governance frameworks (NIST AI RMF, EU AI Act, ISO 42001). • Proven experience in product ownership, agile delivery, and stakeholder management. • Strong understanding of MLOps, LLM security, and AI threat landscape. Preferred Certifications • CISSP / CISM / CRISC • Certified AI Security / AI Governance certifications • Cloud security certifications (e.g., AWS Security Specialty, Azure Security) • Product certifications (e.g., Scrum Product Owner) Show more Show less

12+ years of experience in Cybersecurity, AI/ML Security, Product Ownership, or related domains.

Define and own the end-to-end product vision, roadmap, and lifecycle for AI security solutions. Collaborate with business, technology, and cybersecurity teams to identify secure AI use cases and prioritize delivery. Embed security-by-design and privacy-by-design principles into AI/ML product development. Establish and enforce AI security controls covering model development, deployment, and monitoring. Perform AI risk assessments addressing data privacy, model bias, explainability, and regulatory compliance. Ensure alignment with frameworks such as NIST AI RMF, ISO 42001, and enterprise cybersecurity standards. Lead secure AI product delivery across cloud, on-prem, and hybrid environments. Integrate security controls into MLOps/LLMOps pipelines, ensuring continuous control validation. Drive secure SDLC practices including threat modeling, vulnerability management, and secure deployment. Act as the key interface between Product, Engineering, Cybersecurity, Risk, Compliance, and external vendors. Manage third-party AI solution risk assessments and ensure adherence to security and contractual obligations. Ensure compliance with regulatory requirements (e.g., UAE regulations, GDPR, internal policies). Support internal and external audits, ensuring timely closure of findings and remediation tracking. Maintain AI risk registers, documentation, and governance reporting. Define monitoring frameworks for AI systems including logging, anomaly detection, and abuse prevention. Lead AI-related incident response and root cause analysis. Continuously enhance AI security posture based on emerging threats (e.g., OWASP LLM risks, adversarial AI).