AI Security Manager – Strategy, Growth & Transformation

About the role

Deloitte's Cyber team is seeking an AI Security Manager to lead strategy, growth and transformation initiatives for clients adopting generative AI and agentic systems. The role involves translating business and regulatory objectives into actionable cybersecurity controls and governance frameworks.

Key responsibilities

• Lead AI cybersecurity strategy assessments, governance workshops, and risk operating model design for enterprise clients.
• Translate business objectives, regulatory obligations, and risk appetite into AI governance frameworks, risk taxonomies and control operating models.
• Advise clients on AI security strategy decisions and review governance artifacts, policy documents and risk assessments.
• Manage engagement scope, teams, milestones, quality and client expectations across strategy‑led AI security programs.
• Coordinate with Data, Infrastructure, Identity, Application Security and Security Operations leaders to turn strategic recommendations into technical requirements.
• Shape solutions during pursuits through workshops, executive briefings, proposals and delivery plans, and develop reusable cyber strategy assets.

Required profile

• 6+ years of cybersecurity, risk management or technology consulting experience.
• Experience designing AI governance frameworks, risk operating models or security strategy programs for enterprise clients.
• Ability to travel 25‑50% and work across multiple locations.
• Strong written and verbal communication, attention to detail and ability to lead projects.

Required skills

• Knowledge of AI/ML architectures and risks of generative AI and agentic systems.
• Familiarity with NIST AI Risk Management Framework, ISO/IEC 42001, OWASP Top 10 for LLM Applications, MITRE ATLAS or the EU AI Act.
• Experience with AI cybersecurity controls, governance operating models and risk committees.
• Understanding of governance, risk and compliance platforms or AI governance tools.
• Exposure to machine learning lifecycle tools such as PyTorch, TensorFlow or MLflow.