AI Security Engineer Manager

About the Role

As a Manager in AI Security Engineering you will secure the development and deployment of AI/ML and Generative AI solutions. You will work hands‑on across high‑visibility initiatives, embedding security, trust, and resilience into AI systems while enabling rapid, responsible innovation. Recruiting for this role ends on 9/19/2026.

Key Responsibilities

• Secure, Outcome‑Driven Delivery: Design and deliver AI‑enabled solutions that are secure by design, balancing business value with risk mitigation and protecting data, models, and systems.
• Hands‑On AI Security Engineering: Contribute to architecture, design, and development of AI/ML and GenAI systems with embedded security controls; integrate security across the SSDLC, including code reviews, testing, and deployment; manage AI defensive technologies and their evolving operations.
• AI Risk Identification and Mitigation: Identify and address AI‑specific vulnerabilities such as prompt injection, data leakage, model manipulation, and misuse; implement practical safeguards to ensure system integrity and trustworthiness.
• Technical Leadership and Advocacy: Serve as a trusted technical voice for secure AI engineering, ensuring solutions are feasible, secure, and aligned with business and customer objectives.
• Engineering Excellence with Security Focus: Maintain high standards for code quality, scalability, and security; contribute to secure coding practices, reusable patterns, and continuous improvement across engineering teams.
• Iterative and Responsible Innovation: Support rapid experimentation while applying appropriate security guardrails; enable teams to innovate safely through controlled, risk‑aware development practices.
• Cross‑Functional Collaboration: Partner closely with product, engineering, cybersecurity, and risk teams to embed AI security into solutions, balancing usability, performance, and security.
• Standards and Best Practices: Apply and help evolve standards for AI security, including data protection, access control, model validation, and monitoring within DevSecOps and MLOps pipelines.
• Communication and Influence: Clearly articulate technical risks, trade‑offs, and solutions to both technical and non‑technical stakeholders, contributing to alignment and informed decision‑making.

Required Skills

• 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, dynamic environment
• Strong interpersonal skills and professional demeanor
• Ability to meet deadlines
• Ability to mentor and provide clear guidance to others

Qualifications

• Required: Bachelor’s degree or equivalent in Computer Science, Computer Engineering, Business Administration, or a related field
• Minimum 6 years of relevant experience in software engineering, cybersecurity, and/or AI/ML, with hands‑on delivery experience
• Minimum 1 year of people and/or process management experience
• Preferred: Strong understanding of AI/GenAI technologies and associated security risks (e.g., prompt injection, data exposure, adversarial threats)
• Experience building and securing applications using Python, JavaScript, or similar languages, along with ML frameworks such as PyTorch or TensorFlow
• Familiarity with secure development practices (DevSecOps) and integrating security into CI/CD and MLOps pipelines
• Experience with cloud platforms (AWS, Azure, GCP) and cloud‑native security principles
• Knowledge of data protection, identity/access management, and secure architecture patterns
• Ability to work across teams, mentor engineers, and contribute to a strong engineering culture
• Strong communication skills with the ability to translate technical concepts into business‑relevant insights

Compensation

Estimated salary range: $118,700 – $243,700. The role may also be eligible for a discretionary annual incentive program, subject to program rules and individual/organizational performance.