About Nous Nous is a household AI agent. It takes over the bills and admin people don't have time for and acts for them: switching energy, buying insurance, cancelling forgotten subscriptions, managing the family calendar. Nearly 250,000 UK households have signed up, and another joins every minute. We think the real value of AI isn't writing amazing cover letters, it's doing useful things in the real world for real people. That's the hard part, and a brilliant product is only half of it. An energy switch takes weeks, so our agents run on long-running workflows, not a single chat turn. Cancelling a subscription means a browser agent handling the code Apple sends to your phone. Buying insurance meant getting our regulatory principal comfortable with an agent doing it end to end (a UK first), which comes down to knowing exactly when the LLM should hand over to rules because a mistake would cost someone real money. We're about 30 people running one agent across energy, broadband, mobile, insurance, mortgages and subscriptions (with more being added), each with its own suppliers, rules and ways of going wrong. With far more problems than people, a person or small team owns each one end to end, from spotting it in the data or a customer conversation to shipping the fix. And because the agent acts, you find out quickly whether the fix worked. Everyone builds here: a product engineer launched our subscription cancellation product within a couple of months of joining, and a PM rebuilt our WhatsApp agent. And it's working. We're growing more than 20x year on year, with a market-leading NPS above +80, and we manage well over half a billion pounds of household spending. We've raised more than $30M from Heartcore, Mosaic and a who's who of entrepreneurs who founded Monzo, GoCardless, lastminute.com and Onfido. But the real draw is the team - ask anyone here why they joined and you'll get some version of "to do great work with really smart people". The goal is household life that's simpler, cheaper and fairer, and most of that is still to build. How we build (worth reading before the role) Most companies split the thinkers, the doers and the builders. We don't. Something special happens when they're the same people: a small team that builds and owns the tools for its own problems understands those problems from the inside. So the rule at Nous is simple. The person who feels the problem should be the one who builds the fix. This isn't brand new. A sharp generalist could always wire something together with no-code and low-code tools to solve a problem. The catch was the ceiling: those tools were far more limited than real code, so you hit a wall the moment the problem got interesting. Unless you had superhuman levels of stubbornness and a high tolerance for using tools for things they really weren't designed for. What's changed is that ceiling. With AI tooling and a lot of context, you're now building much closer to real code, and shipping it on the live product. You can change how our WhatsApp agent handles a tricky conversation, dig through Open Banking data to find money we should be saving people, prototype a feature, or automate a process that used to eat someone's week. And you're not doing this around engineering, you're doing it alongside engineers. Engineers build the safe surfaces you ship on (the tools, the infrastructure, the context APIs, the guardrails), and they're who you pull in when you reach the edge of what's safe to touch alone. None of that works without a particular kind of person: not a software engineer, but someone who builds like one. The role You'll own a product surface and make it better, end to end, without waiting for an engineer to do it for you. The clearest version of this already exists on the team. Ben joined as a PM, not an engineer. Engineering set him up with the right infrastructure and a context API, and now he ships changes to Nora (our customer-facing WhatsApp agent) himself, pulling people in only when he's blocked. Worth being upfront: we've never hired for this profile directly before. The people doing it today grew into it here (Ben from product, Gen from ops) once we set them up with the tooling and context to build. You'd be the first we bring in, so expect the role to shift a bit as we figure out what works. Depending on where you're strongest and where we need you most, the first surface might be: • Nora and our AI agents. Find where she struggles in real conversations, improve how she handles them, build and run the evals that tell us whether she's getting better, and tighten the recovery flows for when things go wrong. • Open Banking and subscriptions. Dig into the data behind our subscription product, spot the patterns, and build the logic that decides what's worth cancelling or flagging. Then work out how we cancel them automatically. Real money back in people's pockets. • Whatever's most broken. New products and surfaces appear constantly. You'll take a rough, messy problem and turn it into something shipped and improving. What you'll actually do • Take a product problem from rough to shipped, with AI tooling (Claude Code, Cursor, whatever gets it done) as your main working environment. • Answer your own questions. When you need to know how many members hit a broken flow last week, write the query and find out. Don't file a ticket and wait. • Ship on the safe surfaces: prompts, agent behaviour, configuration, workflows, data pipelines, internal tools. Know where the edge is, and pull in an engineer before you cross it. • Live close to the user. Read the conversations, watch where the product delights people or falls over, and let that drive what you build next. • Own the outcome. A feature isn't done when you've shipped it, it's done when it's working for members. About you You build without precise instructions. You've been a founder, an early PM, or the generalist who ends up owning the thing nobody else will. Give you a problem and some context