Overview As the senior technical owner, you will lead the AI security runtime control plane and enforcement fabric across a multi-cloud estate. You’ll implement inline AI traffic enforcement, tune policies for fast, low-friction security, and act as the escalation point for complex AI security incidents. You’ll drive a closed-loop defensive system that learns from red-team findings to evolve runtime policies and SOC threat models. You will collaborate with cross-functional teams to secure AI and cloud environments, applications, and infrastructure, shaping resilient security at scale.

Compensaciones / Incentivos

elective benefits tailored to country career growth and professional development programs well-being programs and Life Empowerment Assistance diversity, equity & inclusion initiatives onboarding program to connect with colleagues participation in inclusive communities and volunteering initiatives

Responsabilidades

Build and own the AI runtime control plane and inline enforcement pipeline for AI traffic across Azure, AWS, GCP, Copilot Studio, and self-hosted environments Harden gateway layers with buffering, overload management, rate limiting, and prompt-truncation to defend against token-exhaustion and denial-of-service attacks Integrate AI asset context, telemetry, and continuous red-team signals into SIEM/SOC workflows for forensics and audit Author and calibrate runtime policies (prompt-injection/jailbreak defense, PII redaction, data masking, tool-call validation, MCP access control)



Balance detection and hard-block modes per AI archetype to minimize false positives Translate red-team findings into policy updates and new detections; validate with re-testing Lead L3 escalation for AI security toolset, investigate AI-specific attacks, and drive automated containment Evaluate and pilot AI security vendors and proofs-of-concept for runtime defense and model-security platforms Design and maintain secure multi-cloud patterns and least-privilege access across humans, service principals, and agents Embed security into DevSecOps with IaC scanning (Terraform), container/Kubernetes security, secrets management, and pre-deployment gates Support cloud workload vulnerability management and act as escalation for investigations across cloud, identity, endpoint, and AI telemetry

Requisitos principales

Proven hands-on experience securing or operating AI/ML/LLM-based systems Experience deploying, integrating, and tuning security platforms in complex enterprise environments Security tooling experience in Kubernetes (AKS/EKS) and integrating open-source components Proficiency in KQL, PowerShell, Python, Terraform; CI/CD and IaC security Strong understanding of CSPM/CWPP/CNAPP operations and cloud identity/entitlements Excellent English communication and ability to document runbooks and integration guides Bachelor in Computer Science or related field (equivalently demonstrated practical experience) Strong written and verbal communication Cross-functional collaboration Analytical and problem-solving mindset AI/GenAI security depth including prompt-injection/jailbreak defense and RAG security LLM and agentic-AI threat modeling (OWASP LLM Top 10 2025, MITRE ATLAS) AI gateway and runtime enforcement technologies

📌 AI and Cloud Security Engineer - TD Synnex (Barcelona)
🏢 TD Synnex
📍 Barcelona