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About Nous
Nous is an AI agent that takes some of the load of life: making good decisions and acting for people in areas where they're not the experts, or aren't paying enough attention. We started with bills, where we're already saving households thousands, and we're now expanding into new categories. Think Amazon starting with books.
It's working. 20x year-on-year growth makes us one of the fastest-scaling startups in the UK, and an NPS of +70 (higher than Apple) says our users love it. On top of bill optimisation, we've just launched two more products: insurance, where we're the first in the UK to get regulatory approval to run the full discovery-and-purchase journey as an agent (not just hand you a link). And subscription management, where we use Open Banking to actively cancel unwanted subscriptions for people, rather than just draw them a pretty graph.
We're a certified B Corp, and that's how we hold ourselves to the mission rather than just talking about it. We've stacked the deck: a founding team with multiple exits, and investors including the founders of Monzo, Wise, Booking.com, lastminute.com, Onfido, Funding Circle, Tide and Habito.
The problems are hard, and that's the point. Talk is cheap, and that goes for agents too. To have real impact, an agent has to break out of the sandbox and act in the real world, where there are consequences. That means solving all the thorny, frustrating, genuinely interesting problems the real world throws up.
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.
Reasons to use Rodeo
Iโm in my final year doing Economics and I donโt know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer โ it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) donโt need a masters. Letโs look at the ones youโd be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet โ that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant โ 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
Youโve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon โ deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme โ client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right โ and where to focus when applying.
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 and you start building. You don't wait for a spec or a map.
- AI tooling is already how you work. Not "ChatGPT wrote my cover letter". You use Claude Code, Cursor or similar as your working environment: prototyping, querying data, navigating systems, automating your own work. You've felt the shift where one person with the right tools does in an afternoon what used to take a sprint, and you've leaned into it. You're getting a sense of what problems are now much easier, and which aren't.
- You're not a software engineer, and you don't need to be. You're technically fearless yet humble about your limitations. You'll happily get under the bonnet, read enough code to be dangerous, write a bit of SQL, and pick up a new tool before anyone hands it to you. And you have good judgement on when you should ask for help.
- You've got product judgement. You can tell a real problem from a shiny one, you frame things around what changes for the member, and you kill your own ideas as readily as you back them.
- You've been at this a while. You've done the doing long enough to have the scars, and you've owned something real before. This isn't a first job, and you'll be trusted to own a surface early.


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Nice-to-haves:
- You've built and shipped your own thing: a startup, a side project, an internal tool that took off.
- You've worked with LLMs, agents or evals, or with messy real-world data (Open Banking, financial, operational).
- Startup experience where you wore several hats and none of them fit.
How we work
- We keep the middle thin, on purpose. There's barely any middle management, which means fewer bottlenecks and room for exceptional people to have real impact without first being promoted into managing others. It's a real bet, not a free lunch. Instead of a manager buffer, you get lots of context and colleagues who help because they're invested, not because an org chart says so. If you need a clear remit handed down before you can move, this probably won't suit you.
- Your first 90 days are built around getting you to real ownership safely: pairing when you want it, lots of context, and people who want you to ship. We celebrate the person who built the unglamorous version this week, not whoever thought of it first.
- We're office-first, near Farringdon. We do a lot of our best thinking together and being in the same room helps, though we're pragmatic about heads-down work when you need it.
Remuneration and benefits
- Compelling package including share options with life-changing upside. We've raised enough to pay real salaries, and we all share in the upside. If we win, we win together.
- ๐ข A great office set up for collaborative work (we already need more whiteboards)
- ๐ป The equipment, setup and training you need to do your best work
- ๐ค A high-context environment with real exposure to the big decisions, in the room when it happens
- โ Very good coffee
- ๐ฝ๏ธ A well-stocked kitchen (featuring a wildly popular toastie maker)
- ๐ Informal social every week, something bigger every month
- โ๏ธ 33 days paid holiday (including bank holidays)
- ๐ Health and dental cash plans, including an employee assistance programme
- ๐ด Travel benefits, including the cycle-to-work scheme and season ticket loans
If you don't tick every box but think you'd be great at
โIt took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what Iโve been looking for.โ
Jessica, London
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