AI Security Engineer Manager
About the role
As a Manager in AI Security Engineering, you will play a critical role in securing the development and deployment of AI/ML and Generative AI solutions. You will operate 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.
You will bring strong engineering depth and applied AI knowledge, combined with expertise in cybersecurity principles, to design and deliver secure, scalable solutions. This role requires a collaborative, execution-focused leader who can influence teams, mentor engineers, and ensure AI systems meet enterprise security, risk, and compliance expectations.
Impact: This role directly contributes to reducing enterprise risk and strengthening trust in AI systems. Your work will enable secure adoption of AI capabilities while protecting critical assets and maintaining compliance.
The team: Deloitte Technology US (DT - US) helps power Deloitte's success, which serves many of the world's largest, most respected organizations. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence. The ~3,000 professionals in DT - US deliver services including: Cyber Security, Technology Support, Technology & Infrastructure, Applications, Relationship Management, Strategy & Communications, Project Management, Financials. Cyber Security vigilantly protects Deloitte and client data. The team leads a strategic cyber risk program that adapts to a rapidly changing threat landscape, changes in business strategies, risks, and vulnerabilities. Using situational awareness, threat intelligence, and building a security culture across the organization, the team helps to protect the Deloitte brand. Areas of focus include: Risk & Compliance, Identity & Access Management, Data Protection, Cyber Design, Incident Response, Security Architecture, Business Partnership.
Responsibilities
- Secure, Outcome-Driven Delivery: Design and deliver AI-enabled solutions that are secure by design, balancing business value with risk mitigation. Solve complex problems while ensuring protection of data, models, and systems.
- Hands-On AI Security Engineering: Actively 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 the operations of those technologies which will evolve over time.
- AI Risk Identification and Mitigation: Identify and address AI-specific vulnerabilities, including 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. Ensure 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. Balance usability, performance, and security in decision-making.
- 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. Contribute to alignment and informed decision-making.
Requirements
- Bachelor's degree or equivalent in Computer Science, Computer Engineering, or Business Administration.
- 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.