AI Phone - Security & Privacy Engineer

Location: Hybrid in Seoul, South Korea

Company

Building proactive AI-native applications and devices that bring intelligence into everyday conversations, coordination, and workflows.

What you will do

• Design the security and privacy architecture for an AI-native phone, including permission models and access boundaries for AI agents.
• Secure AI access to messages, contacts, calendars, notifications, camera, microphone, location, and other sensitive information through sandboxing and isolation.
• Define authentication, authorization, access-control, audit logging, and user-visible activity tracking for AI tools and application integrations.
• Design encryption, secure storage, data retention, deletion, and personal-data memory mechanisms.
• Identify and mitigate AI-specific risks such as prompt injection, malicious applications, data exfiltration, and unauthorized tool execution.
• Review Android permissions, privileged system access, SELinux policies, and system-level security boundaries; collaborate with Android/AOSP, Agent Runtime, Context & Memory, and Applied ML teams.

Requirements

• Strong experience in mobile security, Android security, application security, or systems security.
• Deep understanding of Android security architecture, including application sandboxing, permissions, SELinux, Binder IPC, and privileged system services.
• Experience designing authentication, authorization, and access-control systems.
• Strong understanding of encryption, secure storage, key management, and data protection.
• Experience with security threat modeling, vulnerability assessment, and penetration testing.
• Understanding of privacy-by-design principles, data minimization, and user consent.
• Ability to work across Android platform, backend, and AI agent architectures.

Nice to have

• Experience with AOSP security customization or Android platform security.
• Experience securing system-level applications or privileged Android services.
• Experience with AI agent security, prompt injection, tool-use security, or LLM data leakage.
• Experience with mobile device security, Trusted Execution Environment, hardware-backed keystores, or secure boot.
• Experience with privacy engineering for products handling sensitive personal information.
• Experience building permission and approval systems for autonomous agents.

Culture & Benefits

• Full-time employment with a hybrid workplace arrangement.
• Security is designed into the product architecture rather than added later.
• Cross-functional collaboration with Android/AOSP, Agent Runtime, Context & Memory, and Applied ML teams.