AI Security Engineer Senior Manager

Deloitte is a leading firm in Cyber and Technology Risk, and they are seeking a Senior Manager in AI Security Engineering to define and lead the firm’s approach to securing AI/ML systems. This role involves shaping the AI security vision, establishing governance, and partnering across various teams to ensure secure deployment of AI technologies.

Responsibilities:

• Contribute to and drive the evolution of the enterprise AI security vision, roadmap, and operating model aligned to broader cybersecurity and AI priorities
• Ensure secure-by-design principles across the AI lifecycle, including model development, data pipelines, deployment, and monitoring
• Establish frameworks to manage AI-specific risks (e.g., model integrity, data leakage, adversarial threats, misuse). Partner with risk and legal to operationalize responsible AI and regulatory compliance
• Guide secure architecture and engineering practices for AI/ML and GenAI platforms, integrating security into MLOps/LLMOps and DevSecOps pipelines
• Define enterprise standards, policies, and controls for AI security, including access, data protection, model validation, and auditability
• Lead, mentor, and scale a high-performing team of engineers and security specialists. Elevate AI security capabilities across the organization
• Balance innovation with risk management—enabling rapid AI adoption while safeguarding enterprise assets, client trust, and brand reputation
• Engage senior leaders across technology, product, risk, and business functions. Communicate clearly on risks, trade-offs, and investment priorities

Requirements:

• Bachelor's degree or equivalent in Computer Science, Computer Engineering, Business Administration
• Minimum 10 years of experience across cybersecurity and software engineering, including AI/ML with increasing leadership responsibility
• Minimum 2 years of people and/or process management experience
• Proven track record defining and implementing security strategies for emerging technologies, including AI/GenAI
• Deep understanding of AI/LLM risks (e.g., prompt injection, data exposure, adversarial attacks) and mitigation approaches
• Experience with cloud-native architecture (AWS, Azure, GCP) and modern engineering practices (DevSecOps, MLOps)
• Strong knowledge of data protection, identity, and governance frameworks, including responsible AI and regulatory considerations
• Demonstrated ability to influence senior stakeholders and lead cross-functional initiatives at scale