Staff AI Product Security Architect at GitLab

Requirements

8+ years of experience in security architecture or application security, with significant experience securing AI/ML systems
Deep understanding of AI system architectures and security vulnerabilities
Proven expertise in threat modeling and security architecture for complex distributed systems
Experience designing security controls for distributed applications and automated workflows
Track record of developing security standards adopted across engineering organizations
Strong knowledge of secure software development lifecycle practices and DevSecOps methodologies
Ability to communicate complex security concepts to diverse technical and non-technical audiences
Experience with AI frameworks, agent architectures, and orchestration platforms
Demonstrated ability to balance security requirements with business objectives
Strong collaborative skills with experience influencing technical decisions across organizations

Experience with AI workflow validation, agent testing, and monitoring approaches
Knowledge of AI regulatory compliance and governance frameworks
Programming skills in Python with hands-on experience in AI frameworks
Security certifications such as CISSP, CCSP, or similar
Experience with GitLab or similar DevSecOps platforms
Background in software engineering with expertise in distributed systems
Published work or presentations on AI security architecture

Design and implement security architectures for AI integrations, including agent security, prompt injection prevention, and workflow validation
Establish secure-by-design principles and patterns for AI systems that enable engineering teams to build secure capabilities efficiently
Conduct comprehensive threat modeling and risk assessments for AI features and multi-agent orchestration platforms
Develop security standards for AI model integration, data handling, and agent communication protocols
Provide expert consultation to engineering teams on AI security architecture decisions and trade-offs
Create architectural documentation and reference implementations that accelerate secure AI development
Stay current with AI security threats, vulnerabilities, and industry best practices to inform architectural decisions
Collaborate with Security Research to translate vulnerability findings into architectural improvements
Partner with Product and Engineering leadership to balance security requirements with product velocity
Mentor engineers and security team members on AI security architecture principles
Work with legal and compliance teams to ensure AI systems meet regulatory requirements including EU AI Act, NIST AI RMF, and data privacy regulations
Contribute to industry thought leadership through technical documentation, standards development, and community engagement