Director of AI Security

Role Overview

• Develop and implement a comprehensive AI security and governance strategy aligned with enterprise objectives and regulatory expectations
• Partner with AI, IT, and Risk leaders to embed security-by-design across the AI lifecycle
• Establish AI threat modeling and risk management frameworks covering confidentiality, integrity, availability, and fairness of AI systems
• Oversee implementation of technical controls to safeguard AI/ML systems from adversarial attacks, data poisoning, model inversion, and prompt injection
• Define standards for secure model development, training, and deployment across cloud and edge environments
• Implement continuous monitoring for model drift, bias, and anomalous outputs
• Lead development of AI security policies, model documentation, and audit processes
• Ensure compliance with emerging AI regulations and frameworks
• Partner with legal, compliance, and data privacy teams to address ethical AI, explainability, and accountability requirements
• Work closely with data science, engineering, and DevSecOps teams to integrate secure development pipelines
• Collaborate with enterprise architecture and identity teams to enable trusted AI infrastructure and secure data access
• Represent AI security strategy in executive briefings, board updates, and regulatory engagements
• Participate in the AI Governance Committee
• Stay ahead of evolving AI and cybersecurity threat landscapes
• Lead red teaming and penetration testing of AI systems to evaluate resilience
• Champion responsible AI initiatives, fostering a 'secure and trusted AI' culture across the organization

Requirements

• Bachelor’s or Master’s degree in Cybersecurity, Computer Science, Artificial Intelligence, or related field
• 10+ years in cybersecurity, including 3–5 years leading AI/ML or emerging technology security programs
• Proven experience designing and implementing secure AI architectures and governance frameworks
• Deep understanding of AI/ML systems, LLMs, data pipelines, and cloud-based AI services
• Familiarity with adversarial ML, data privacy, model security, and AI red teaming
• Knowledge of AI risk management standards (e.g., NIST AI RMF, ISO/IEC 27090x/42001)
• Strong background in cyber defense, threat intelligence, and secure software development (DevSecOps/MLOps)

Tech Stack

• Cloud
• Cyber Security

Benefits

• generous, flexible vacation policy
• educational assistance
• comprehensive health benefits
• 401(k) employer match
• leadership and technical development academies