Product Security Architect

About the role

Logitech's product ecosystem spans embedded hardware, desktop software and cloud services, and security is central to its work. As Product Security Architect, you will cover internally built and self-hosted applications, giving security architecture guidance, threat modeling expertise and hands-on consultancy to engineering teams across product and enterprise software. You will work with Product Managers, engineers and other security colleagues, using technical expertise and AI-assisted tooling to embed security early and at scale.

Key responsibilities

• Define and own secure architecture standards across in-house and self-hosted applications, and establish secure communication pathways, trust boundaries, authentication frameworks and cryptographic standards.
• Create reusable, scalable security patterns that engineering teams can adopt without slowing delivery.
• Lead threat modeling for new and existing products, identify architectural risks early in the SDLC and maintain a living view of the internal threat landscape.
• Act as security partner for Product Managers, Lead Engineers and Engineering Directors during ideation and design, running security reviews and defining testing scopes and critical attack paths.
• Be the primary security authority for AI features, including on-device ML models, cloud-hosted LLM integrations and AI data pipelines, setting guardrails against prompt injection, insecure output handling and training data exposure.

Required profile

• 6+ years in Application Security, Product Security or Security Architecture roles across a diverse software portfolio.
• Experience designing secure architectures for both product-facing and enterprise internal applications.
• Track record of influencing engineering culture and embedding security early in development.
• Exceptional communication skills and a consultancy mindset that builds trust without authority.

Required skills

• Threat modeling and secure SDLC frameworks (OWASP SAMM or equivalent).
• Authentication and authorization (OAuth 2.0, OIDC) and secure API design.
• Cryptography fundamentals and cloud-native security (AWS, GCP or Azure).
• Use of AI and LLM tools for threat modeling and architecture reviews, and awareness of AI/ML security risks.