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

Benefits

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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

cloud security architectureIAMnetwork segmentationencryptionsecure design patternsDevSecOpsInfrastructure-as-Code (IaC)container technologiesAI/ML securityautomation frameworks

Soft Skills

technical leadershipmentorshipinfluencecollaborationcommunication