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.