AI & Product Security Leader

We are seeking a visionary and deeply technical AI & Product Security Leader to architect and execute our global enterprise AI security strategy. In this high-impact position, you will serve as the primary authority for secure AI adoption, safeguarding internal systems, product architectures, and third-party AI integrations. You will inherit, scale, and mentor a high-caliber Application Security team while establishing cutting-edge defense mechanisms against emerging adversarial machine learning threats.

Core Responsibilities

• Strategic Governance: Formulate and drive the corporate roadmap for secure and responsible AI adoption, defining operational standards, priorities, and execution frameworks.
• Team Scaling & Leadership: Manage, recruit, and develop a specialized Application Security unit, direct-managing senior engineers and dedicated AI security functions.
• Architectural Guardrails: Drive risk-based decision-making by embedding security into the core AI lifecycle through threat modeling, rigorous design reviews, and automated controls.
• Adversarial Defense: Establish robust testing capabilities, including specialized red-teaming and simulation frameworks targeted at GenAI risks, data leakage, and model manipulation.
• Vendor & Third-Party Risk: Design and enforce rigorous security evaluation metrics for integrating external AI vendors and SaaS-based LLM platforms.
• Crisis Management: Provide executive and technical leadership during complex security incidents, orchestrating real-time responses and post-mortem optimizations.
• Executive Influence: Act as the organization's corporate authority on AI risks, representing the cyber division in executive forums and aligning strategies with executive leadership (VP/C-level)

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What You’ll Bring

• Industry Veteran: 10+ years of professional cybersecurity experience, featuring a proven track record of 3–5 years heading a global domain (e.g., Product Security, AppSec, or DevSecOps leadership).
• Application Security Depth: Deep expertise in secure SDLC infrastructure, API protections, threat modeling, and modern cloud topologies (AWS, GCP, or Azure).
• AI/GenAI Security Practice: Practical experience analyzing or hardening LLM-native applications against risks like prompt injection, inversion, data poisoning, and compliance gaps.
• System Assessment: Demonstrated ability to perform comprehensive architectural audits on highly complex, distributed data networks, translating flaws into practical engineering roadmaps.
• People Management: Natural leadership skills with experience managing elite security architects, red-teamers, or vulnerability researchers.
• Stakeholder Management: Exceptional communication skills with the ability to influence cross-functional business partners and present complex technical risk postures in high-pressure executive rooms.

Education: B.Sc. in Computer Science, Cyber Security, Software Engineering, or a matching technical discipline (Advanced degrees/certifications are a distinct advantage).