AI Phone - AI Systems / Agent Architect
On-siteUnited KingdomFull Time
- Posted
- today
- Source
- Arbeitnow
- Field
- Engineering
Skills
SecurityREST APIsLLMsAI
Description
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
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Define the overall AI architecture for the phone.
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Design how AI agents interact with the OS and applications.
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Define agent runtime and orchestration architecture.
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Design context and memory systems that allow AI to understand user activities, preferences and ongoing tasks.
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Define how agents execute multi-step workflows across different applications.
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Design long-running task execution, state management and recovery mechanisms.
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Define model routing between on-device and cloud models.
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Evaluate the feasibility of running different AI capabilities locally versus remotely.
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Work with Android engineers to define the interfaces required for system-level AI execution.
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Establish reliability, observability and evaluation standards.
Requirements
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Strong backend and distributed systems engineering experience.
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Experience building production AI agent systems or complex orchestration systems.
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Strong understanding of LLMs, tool calling, structured outputs and agent execution.
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Experience with stateful workflows and multi-step task execution.
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Experience with context engineering, retrieval and memory systems.
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Strong system design and architecture skills.
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Ability to work across backend, AI and platform engineering.
Nice to have
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Experience building AI assistants or agent platforms.
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Experience with long-running autonomous workflows.
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Experience with model routing and inference optimization.
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Experience with on-device AI or hybrid local/cloud architectures.
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Experience with permission-aware tool execution and agent security.
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