Staff Security Architect

Description

The company behind the PlayStation brand, a subsidiary of Sony Group Corporation, makes hardware and network services used by more than 100 million people and creates entertainment built on well-known intellectual properties.

The team sits within Security Architecture, working across cloud, AI security and enterprise platforms.

The role shapes the security of enterprise, cloud, platform and AI-enabled technology. You will work with engineering, infrastructure, product and security teams to find systemic risk, build scalable security patterns and guide the secure adoption of new technology, including generative AI and agentic systems. The environment is complex and global, and the role carries real influence over technical direction.

Responsibilities

• Design, review and approve security architecture for enterprise, cloud, SaaS, platform and application environments, weighing business goals, engineering limits and risk.
• Lead cloud security architecture on AWS, Google Cloud and hybrid setups. Cover identity, network security, data protection, logging and monitoring, key management, workload isolation, security posture management, and the use of native and third-party cloud controls.
• Define and review security architecture for SaaS and PaaS platforms. Cover identity federation, privileged access, tenant configuration, data protection, API and integration security, logging, third-party risk and secure use of enterprise SaaS.
• Build security into the full software delivery lifecycle: source control, CI/CD pipelines, build systems, artifact repositories, infrastructure as code, secrets management, code and artifact signing, software provenance, deployment automation and developer platform controls.
• Lead security architecture for AI-enabled systems, including generative AI, large language models, retrieval-augmented generation, AI agents, model-serving platforms and AI-assisted developer workflows.
• Design mitigations for prompt injection, insecure tool use, excessive agency, sensitive-data disclosure, model or supply-chain compromise, unsafe output handling and abuse of AI services.
• Set security requirements for AI data, models, prompts, embeddings, vector stores, APIs, tools and agent identities. Cover least-privilege access, secrets, encryption, isolation, provenance, logging, monitoring and lifecycle controls.
• Architect and improve identity, authentication, authorization, network security, key management, cryptography, application security and production security controls in complex environments.
• Find security design gaps in existing and proposed systems. Turn them into practical improvements: architecture changes, reference patterns, hardening standards, preventive controls and responsible automation that makes security more repeatable and effective.
• Lead technical work across multi-disciplinary teams. Explain risks, tradeoffs and recommended solutions to engineering leaders, business stakeholders and non-security audiences.

Requirements

• 15+ years of relevant experience in security architecture, security engineering, product security, cloud security, infrastructure security or a related field, with proven leadership at senior or staff level.
• Deep knowledge of security architecture across cloud, application, network, identity, platform, infrastructure and enterprise environments.
• Hands-on experience designing or securing cloud-based and containerized environments, including AWS or Google Cloud.
• Solid understanding of modern identity and access management, PKI, OAuth/OIDC, SAML, TLS, VPNs, secrets management, key management systems, cloud KMS and HSMs.
• Expertise in network and application security controls, such as WAFs, NGFWs, segmentation, DMZ design, DDoS mitigation, load balancing, proxies, intrusion detection and prevention, and host-based controls.
• Experience with secure software development, threat modeling, CI/CD and developer platforms, application security and engineering mitigations across the software lifecycle.
• Working knowledge of AI and ML security. You can assess risks in generative AI, LLM and agentic architectures, including data flows, trust boundaries, model access and tool integrations.
• Strong critical thinking, risk prioritization, communication and influence skills. You can lead through ambiguity and work across global, cross-functional teams.
• Bachelor's degree in Computer Science, Mathematics, Engineering, Information Security or equivalent practical experience.
• Preferred: experience securing AI/ML platforms, generative AI applications, model gateways, RAG architectures, vector databases or agentic workflows in production.
• Preferred: experience with AI security evaluation, red teaming, adversarial testing, model abuse testing or control validation for AI-enabled systems.
• Preferred: experience securing large-scale Linux, distributed, multi-tenant or high-availability production environments.
• Preferred: development or automation experience in Python, C++, Java or similar languages.
• Preferred: recognized technical leadership through patents, publications, open-source work, conference talks, teaching or security community involvement.
• Preferred: penetration testing, adversarial security or attacker-minded design experience.
• Preferred: Master's degree or Ph.D. in Computer Science, Mathematics, Engineering, Information Security or a related field.

Conditions

The company runs background checks at the offer stage for all new employees, which may include criminal background checks for some roles, and processes personal information for this purpose.