Staff Cloud Security Engineer

Role Overview

• Provide cloud security capabilities that are proactive, preventive-focused models that address modern threats, including those driven by AI-enabled attack techniques
• Expanding into next-generation security domains such as AI/ML security, container security, and advanced threat detection and response
• Define and drive cloud security strategy, architecture standards, and technical roadmaps across cloud and AI-enabled environments
• Lead the design and implementation of preventative security controls, leveraging automation and AI-driven capabilities to reduce risk and improve detection and response
• Architect and secure complex multi-cloud and hybrid environments across AWS, Azure, GCP, and on-premise infrastructure
• Define and implement security architecture for AI/ML workloads, including model pipelines, data protection, and AI-integrated applications
• Identify and establish controls to mitigate AI-specific risks such as prompt injection, data poisoning, model leakage, and adversarial inputs
• Influence security and engineering practices across multiple teams and departments, driving adoption of secure-by-design principles
• Own the security outcomes of key cloud and AI initiatives, ensuring successful delivery and measurable risk reduction
• Establish and evolve DevSecOps and Infrastructure-as-Code (IaC) security standards, integrating security controls into CI/CD pipelines at scale
• Drive adoption and optimization of CNAPP platforms and related tooling to improve risk visibility and remediation across cloud, container, and AI environments
• Define and implement security architecture for containerized platforms (Kubernetes/EKS/GKE/AKS), including cluster hardening, workload isolation, image supply chain security, and runtime protection controls
• Lead the evolution of detection and response capabilities, integrating cloud telemetry, Cloud EDR, and advanced security analytics
• Conduct and guide threat modeling and risk assessments (Attack Surface Management, Data Security Posture Management, etc.) for complex cloud-native and AI-enabled systems
• Architect and deliver automation frameworks and security services to improve scalability and operational efficiency
• Provide technical leadership and mentorship to engineers, influencing department-level goals and technical direction

Requirements

• Bachelor’s or Master’s degree in Computer Science, Information Security, or related field (or equivalent experience); typically 12+ years of relevant experience
• 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
• Strong programming and automation experience, with the ability to design and scale security engineering solutions
• Extensive experience implementing DevSecOps practices and securing Infrastructure-as-Code (IaC) workflows
• Expertise working with container technologies (Kubernetes, Docker, EKS, GKE, AKS)
• Deep understanding of security risks in AI/ML systems, including prompt injection, data poisoning, model leakage, and adversarial inputs
• Experience defining and securing AI/ML architectures, including training pipelines, inference systems, and AI-integrated applications
• Strong knowledge of data security and privacy controls in AI systems

Tech Stack

• AWS
• Azure
• Cloud
• Docker
• Google Cloud Platform
• Kubernetes

Benefits

• medical
• dental
• vision
• matching 401(k)
• paid time off
• wellness program
• coveted employee discounts for Sony products
• bonus package