Staff Cloud Security Engineer

About the role

Join the Security Engineering team at SIE as a Staff Cloud Security Engineer. In this highly technical role, you will assist in the planning, design, development, testing, and management of security tools and controls for our cloud environments. You will define and drive cloud security strategy, architecture standards, and technical roadmaps across cloud and AI-enabled environments. Additionally, you will lead the design and implementation of preventative security controls, architect and secure complex multi-cloud and hybrid environments, and influence security and engineering practices across multiple teams and departments. Key missions: Assister à la planification, à la conception, au développement, aux tests et à la gestion des outils et contrôles de sécurité pour protéger les environnements cloud.. Définir et conduire la stratégie de sécurité cloud, les normes d'architecture et les feuilles de route techniques à travers les environnements cloud et alimentés par l'IA.. Diriger la conception et la mise en œuvre de contrôles de sécurité préventifs, en tirant parti de l'automatisation et des capacités alimentées par l'IA pour réduire les risques. Profile: - Proven experience defining and securing large-scale cloud and hybrid architectures (AWS, Azure, GCP, On-Premise) - Deep expertise in cloud security architecture, including IAM, network segmentation, encryption, and secure design patterns - Expertise working with container technologies (Kubernetes, Docker, EKS, GKE, AKS) - Bachelor’s degree or equivalent in Computer Science, Information Security, or related field - Extensive experience implementing DevSecOps practices and securing Infrastructure-as-Code (IaC) workflows - Strong programming and automation experience, with the ability to design and scale security engineering solutions - Strong knowledge of data security and privacy controls in AI systems - Familiarity with frameworks such as OWASP Top 10 for LLMs and NIST AI Risk Management Framework - Experience defining and securing AI/ML architectures, including training pipelines, inference systems, and AI-integrated applications - Experience securing advanced AI patterns such as LLM integrations, APIs, MCPs, RAG pipelines, or model services (preferred) - Deep understanding of security risks in AI/ML systems, including prompt injection, data poisoning, model leakage, and adversarial inputs - Deep understanding of cloud detection and response, IaC scanning, and runtime protection - Experience influencing technical direction across multiple teams or departments - Experience designing highly scalable, resilient, and secure architectures across application, network, and data layers - Experience working across multi-OS and distributed environments - Experience leading implementation and adoption of CNAPP platforms - Strong background in security prevention, detection, and response strategy - Relevant certifications (e.g., ISC2, GIAC, AWS, Azure, GCP) preferred