£125k - £185k
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172,000+ live jobsProduct Engineer, AI
On-site in London·Full-time·Added today (last checked 9 Nov)
Our summary
- Salary
- £148,000 - £220,000 a year
About £7,520 - £10,700 a month after tax.
- Work mode
- On-site, London
- Contract
- Full-time
- Experience
- 4+ years
- Holiday
- Unlimited holiday





Skills
Nice to have
Requirements
What we're looking for
- 4+ years shipping full-stack product, with strong front-end skills (TypeScript and React or similar).
- A habit of prototyping: you'd rather show a working idea than describe one.
- Experience building, or strong interest in building, AI-powered interfaces: streaming responses, async jobs, generative UI.
- Obsession with the user experience: you care about the details users feel and what makes a product great.
- Ownership of what you ship, from first idea to customers using it.
- 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
- You've shipped something people loved enough to tell others about, at a startup or on your own.
- You've built rich data visualization or real-time interfaces.
- You've built prototypes or side projects with AI coding agents that real people use.
Pay & benefits
What you'll get
- 🏖️ Unlimited PTO and sick leave
- 🍽️ Free lunch, snacks, and coffee
- 🚀 Professional Development Stipend
- ✈️ Annual company retreat
- 🛠️ Hardware sensor stipend
- 📈 Employee-friendly equity terms
- 🏢 In-office 5 days per week
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
The base pay range for this role is £148,000 - £220,000 per year.
The role
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.
What you'll do
As an AI Product Engineer, you'll bring new ideas to life: prototype fast, put them in front of real engineers, and turn the ones that work into polished products where engineers and agents work together.
- Prototype new features and interactions quickly, often with AI coding agents, to test ideas with real users before committing.
- Build where engineers and agents work together, end to end: the interface, the APIs behind it, and how agent work streams in and stays editable.
- Make agent work trustworthy on screen: visible steps, citations, and clean handoffs back to the engineer.
- Own product decisions in your area, from what to build to when it's ready.
- Watch real users, sweat the details, and keep iterating on what you learn.
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