AI Phone - AI Systems / Agent Architect

About

We are reimagining the phone. AI phones need to be proactive, intuitive, intelligent and low cost. This is a mission critical for rest of the world to adopt intelligence.

There are over 5 billion people using everyday applications such as email, messaging, notes, tasks, and calendars, yet most are not AI-native. Our mission is to build proactive applications and devices that bring intelligence into daily conversations, coordination and workflows, with minimal prompting.

Focus

Agent runtime, context, memory, orchestration and overall AI system architecture.

Responsibilities

• Define the overall AI architecture for the phone.
• Design how AI agents interact with the OS and applications.
• Define agent runtime and orchestration architecture.
• Design context and memory systems that allow AI to understand user activities, preferences and ongoing tasks.
• Define how agents execute multi-step workflows across different applications.
• Design long-running task execution, state management and recovery mechanisms.
• Define model routing between on-device and cloud models.
• Evaluate the feasibility of running different AI capabilities locally versus remotely.
• Work with Android engineers to define the interfaces required for system-level AI execution.
• Establish reliability, observability and evaluation standards.

Requirements

• Strong backend and distributed systems engineering experience.
• Experience building production AI agent systems or complex orchestration systems.
• Strong understanding of LLMs, tool calling, structured outputs and agent execution.
• Experience with stateful workflows and multi-step task execution.
• Experience with context engineering, retrieval and memory systems.
• Strong system design and architecture skills.
• Ability to work across backend, AI and platform engineering.

Nice to have

• Experience building AI assistants or agent platforms.
• Experience with long-running autonomous workflows.
• Experience with model routing and inference optimization.
• Experience with on-device AI or hybrid local/cloud architectures.
• Experience with permission-aware tool execution and agent security.