AI Security Architect

About the role

In this role you will build the foundations of a secure AI program from the ground up, working at the intersection of security architecture, cloud engineering, and artificial intelligence. You will treat AI security as an engineering discipline — grounded in clear architecture, recognized frameworks, and well-defined controls — and translate it into concrete, actionable work that engineering teams can implement, test, and continuously improve. You will primarily work with AI and LLM-based workloads, including the newest models deployed in isolated cloud environments, defining how they are designed, deployed, monitored, and governed, with a strong focus on guardrails, threat models, isolation requirements, and logging and monitoring standards.

Responsibilities

• Build the foundations of the AI-based security program, including the roadmap, governance, and approval processes
• Define how AI can be safely used for security testing, such as AI-assisted code scanning and vulnerability discovery, including validation of findings and their integration into the vulnerability management process
• Define the AI security architecture and select and adapt the most suitable AI security frameworks
• Design threat models for AI workloads and define security controls for AI environments
• Design reference architectures for secure AI platforms deployed across AWS and GCP
• Define secure operating principles, deployment standards, and isolation requirements for frontier models
• Design guardrails, along with monitoring and logging requirements for AI systems
• Translate architecture and standards into an implementation backlog for engineering teams and support its delivery

Requirements

• 7+ years in security architecture or cloud security, designing and securing complex, multi-cloud environments
• Proven hands-on experience securing AI/ML and LLM-based systems, including data, model, and infrastructure layers, and implementing effective containment measures for security incidents
• Strong knowledge of AI-specific threats such as prompt injection, data leakage, model abuse, and agent/tool misuse
• Understanding of AI infrastructure components, including model hosting, vector databases, orchestration frameworks, and AI gateways
• Experience conducting security assessments, adversarial testing, threat modeling, or red-team style evaluations of AI systems
• Familiarity with AI security frameworks and standards, such as NIST AI RMF, OWASP Top 10 for LLM Applications, MITRE ATLAS, and ISO/IEC 42001
• Experience with threat modeling and designing security controls, guardrails, and isolation for complex workloads
• Solid cloud security background in GCP and/or AWS, including IAM, network isolation, containers, and logging
• Experience defining security telemetry and detection use cases and integrating logs into SIEM or real-time analytics platforms
• Ability to turn strategy into actionable engineering requirements
• Strong communication and stakeholder management skills, fluent English