Staff Software Engineer, Agents - UK

United Kingdom·Londonfull-timelead

Software EngineerSoftware Engineering

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Quick Summary

Key Responsibilities

orchestration, planning, tool calling, memory, and background agents that run long investigations on their own. Own the shared tool layer that our agents and external agents (via MCP) both use,

Technical Tools

Software EngineerSoftware Engineering

Engineers today are building some of the most ambitious machines humanity has ever seen. They should have AI that’s purpose-built for them.

Nominal is building the Hardware Intelligence Platform that gives engineers increased visibility into complex physical systems, helps them make better decisions, and ultimately gets their products into the real world faster. It brings together the systems, data, intelligence, and applications hardware engineering requires to meet the AI moment. Hardware engineering teams use Nominal to simulate, test, manufacture, and operate the physical systems that keep the world moving, from spacecraft and autonomous vehicles to next-generation energy systems and robotics.

Our customers span aerospace, defense, manufacturing, transportation, energy, and robotics. They include Anduril, Shield AI, Wisk Aero, Pratt Miller Motorsports, Antares, and Shinkei Systems, amongst others, alongside programs within the U.S. Air Force and Navy. Our team draws from SpaceX, Palantir, Anduril, Applied Intuition, Tesla, and other leading companies, united by a common mission: giving hardware engineers the tools to build the future with speed, safety, and confidence. We're a fast-moving team that owns problems end-to-end, works across disciplines, and thrives at the intersection of hardware and software.

Some of the world’s leading technology investors, including Sequoia, Lightspeed, Founders Fund, General Catalyst, Lux Capital, and Insight Partners, are backing Nominal’s ambition to change how machines are built and operated. We’re looking for engineers who want to take on hard problems and help make a new generation of world-changing hardware possible.

We're the team behind Nominal's agents, AI-native applications, and MCP, and its forward-leaning AI bets. Our mission is to unlock the bottlenecks of the hardware lifecycle with AI. Our agents reason over physical reality, from high-rate telemetry and test campaigns to designs and simulations, where real test results are the ground truth their work is checked against. We believe opinionated AI, built for the real work of hardware programs, will change how the world engineers.

We're collaborative, iterative, and high-agency, and we're human-centered and customer-focused. We build with the newest AI tools every day, and because those tools keep changing, so do we: we stay curious and keep looking for the better way. Our team spans data science and ML, distributed systems, search, and knowledge systems, and we obsess over how agents can be genuinely useful to the engineers who rely on them.

As a Staff Engineer supporting agents, you'll design how Nominal's agents work: you'll architect the one platform our agents, the Nominal MCP, and our internal agent all run on, and set technical direction for the team that builds on it.

Responsibilities

~1 min read

→Design and build the agent harness: orchestration, planning, tool calling, memory, and background agents that run long investigations on their own.
→Own the shared tool layer that our agents and external agents (via MCP) both use, so every capability we build works everywhere.
→Build how agents assemble context: retrieval across test data, documents, designs, and simulations, including sensor data far too large to fit in a context window.
→Make model choice a decision, not a dependency: routing, cost, latency, and fallbacks across frontier models.
→Partner with evals to make quality measurable, and with the platform team on how the context layer grows.
→Set the architecture other engineers build on, and raise the bar through design reviews and mentorship.

8+ years building production systems, including real experience shipping LLM or agent systems to users.
Strong distributed-systems and backend fundamentals; you've owned systems where reliability mattered.
Opinions about agent architecture (tool design, context management, autonomy, failure handling) and the judgment to change them when data says so.
A track record of setting technical direction across a team and raising the bar for the engineers around you.
You build with modern AI coding agents (Claude Code, Cursor, Codex) every day, and stay curious and open to better ways of working. The tools keep changing, and so do we.

Nice to Have

~1 min read

You've built an agent harness or LLM platform that other engineers or customers build on, at an AI-native company.
You've shipped long-running, autonomous agents to production and know where they break.
You've contributed to MCP, agent frameworks, or open-source LLM infrastructure.
You've built software for physical systems: robots, vehicles, aircraft, or the test stands behind them.