AI Security Engineer Senior Manager

Senior Manager role focused on defining and leading the firm's approach to securing AI/ML and Generative AI systems at scale. The role involves shaping AI security vision, establishing governance and controls, and embedding security into the AI lifecycle across product, engineering, risk, and legal teams. It requires guiding secure architecture, driving standards, and mentoring a team to enable secure adoption of AI technologies while managing enterprise risk and regulatory compliance.

What you'd actually do

  1. Contribute to and drive the evolution of the enterprise AI security vision, roadmap, and operating model aligned to broader cybersecurity and AI priorities.
  2. Ensure secure-by-design principles across the AI lifecycle, including model development, data pipelines, deployment, and monitoring.
  3. 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.
  4. Guide secure architecture and engineering practices for AI/ML and GenAI platforms, integrating security into MLOps/LLMOps and DevSecOps pipelines.
  5. Define enterprise standards, policies, and controls for AI security, including access, data protection, model validation, and auditability.

Skills

Required

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

What the JD emphasized

  • securing AI/ML and Generative AI systems at scale
  • operationalize responsible AI and regulatory compliance

Other signals

  • securing AI/ML and Generative AI systems at scale
  • embedding security and trust into the AI lifecycle
  • secure architecture and engineering practices for AI/ML and GenAI platforms
  • operationalize responsible AI and regulatory compliance