Drimva

Snap

Software Engineer, Device Security, Level 4

$133K–$235K

San Diego, California +1 · Full-time · Posted Oct 26, 2026

Location
San Diego, California
Los Angeles, California
Experience
2+ years required; 5+ years of production software development is preferred.
Education
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, a related technical field, or equivalent practical experience; Master’s degree or PhD preferred.

About the job

Build and harden security and privacy systems for Specs devices, including protections for on-device AI across Snap OS, firmware, applications, and connected services.

What you'll do

  • Design on-device security systems, including permissions, access control, secure IPC, sandboxing, and trusted execution boundaries.
  • Develop privacy and security controls for on-device AI and protect device, sensor, and user data.
  • Improve fuzzing, automated security testing, and continuous validation for operating-system, firmware, and AI-related components.

What they ask for

  • Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, a related technical field, or equivalent practical experience.
  • 2+ years of experience building security, privacy, or platform protection features for Linux-based, embedded, mobile, wearable, or connected device systems.
  • Experience with applied cryptography, authentication, authorization, secure communications, key management, threat modeling, vulnerability assessment, or system security for embedded or Linux-based systems.

Nice to have

  • Master’s degree or PhD in a related technical discipline.
  • 5+ years of production software development experience in languages such as C, C++, Rust; experience in device security, on-device AI, or platform hardening is also preferred.

Pay

$157,000-$235,000 annually USD base salary; $149,000-$223,000 annually USD base salary; $133,000-$200,000 annually USD base salary

Tools

Linux, Snap OS, C, C++, Rust

AI focus

Develop security and privacy controls for on-device AI, including model integrity, sensitive-data handling, inference-time privacy, and local policy enforcement.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 4, 2026 (UTC)