Lead AI Application Security Engineer

GXO Logistics, Inc. is a leading provider of cutting-edge supply chain solutions. As the Lead AI Application Security Engineer, you will serve as the technical lead for securing GXO's Enterprise AI Platform and AI-powered applications, defining AI security architecture and collaborating with various teams to ensure secure deployment and operation of AI solutions.

Responsibilities:

• Lead security testing and AI red teaming for GXO's AI applications, including LLMs, agentic AI systems, ML models, and the Enterprise AI Platform, identifying risks across prompt injection, model manipulation, data leakage, RAG pipelines, and AI supply chains
• Design, implement, and maintain AI-aware DevSecOps practices by integrating AI security controls into CI/CD pipelines, cloud infrastructure, model deployments, and runtime environments
• Develop and maintain secure AI development standards, threat models, and security architecture for AI/ML workloads, ensuring alignment with industry frameworks and GXO security policies
• Evaluate, implement, and manage AI security tooling, including AI firewalls, prompt injection detection, runtime protections, model scanning, and AI security automation while supporting build-versus-buy decisions
• Partner with application, cloud, infrastructure, data engineering, and Information Security teams to integrate AI security into enterprise architecture, platform development, incident response, governance, and continuous improvement initiatives

Requirements:

• Bachelor's degree in Computer Science, Cybersecurity, Information Technology, Engineering, or equivalent related work or military experience, along with relevant AI, cloud, or application security certifications
• 7+ years of experience in application security, DevSecOps, cloud security engineering, or security engineering with progressive technical leadership responsibilities
• Hands-on experience securing AI/ML platforms, LLM applications, agentic AI systems, or enterprise AI infrastructure
• Strong expertise in application security, secure CI/CD pipelines, Kubernetes, container security, API security, Infrastructure-as-Code, cloud security, and DevSecOps practices
• Experience with Google Cloud Platform security, including Vertex AI, GKE, IAM, KMS, VPC Service Controls, Cloud Logging, and cloud-native AI workloads
• Deep understanding of AI security frameworks and methodologies, including OWASP Top 10 for LLMs, OWASP Agentic Applications, MITRE ATLAS, NIST AI RMF, AI threat modeling, prompt injection defense, model supply chain security, and AI red teaming
• Experience securing AWS, Azure, OCI, or hybrid cloud environments, including enterprise identity and access management platforms and Snowflake security
• Experience with AI security tooling such as NVIDIA Garak, Microsoft PyRIT, Promptfoo, Wiz, Checkmarx, Invicti, or similar AI security platforms
• Knowledge of EU AI Act requirements, AI governance, model lifecycle security, MLOps/LLMOps, Lean automation, and enterprise AI compliance frameworks