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A frontier AI company is building systems that can act in the physical world, experimenting, engineering, and executing multi-step processes with real-world constraints. Backed by major research funding and operating at the edge of physical-AI innovation, theyre creating capabilities that dont exist anywhere else. Join to work from first principles, own high-impact systems end-to-end, and help define how agentic AI will operate complex workflows in the real world.
Why This Role Matters
Build agent systems that plan, execute, and recover across intricate engineering workflows
Shape foundational behaviour patterns for next-gen LLM tool-use
Join early enough to influence architecture, culture, and performance standards
Work on problems that sit far beyond typical LLM app engineering
What Youll Do
Develop planners, state machines, and tool-calling flows using frameworks like LangGraph
Create schemas, action definitions, and cross-tool interfaces for reliable, traceable execution
Build error-handling, timeouts, retries, rollbacks, and replay mechanisms
Partner with ML, infra, and systems teams to integrate agents into real engineering toolchains
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What You Bring
Strong experience with agent systems, structured tool calling, or orchestration frameworks
Deep intuition for schemas, deterministic execution, and multi-step workflow design
Ability to model failure modes, edge cases, and safe interactions in complex systems
Comfort working across AI, systems engineering, and specialised domain tools in a high-precision environment