Operations & Automation Associate
Nous
| Company | Nous |
| Category | Operations & Admin |
| Location | London |
| Remote | Hybrid |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 15 May 2026 |
| Last verified | 1 Aug 2026 |
| Source | Employer career page (ashby) |
Description
ABOUT NOUS
Nous is an AI agent that takes some of the load of life; making good decisions and acting for our users in areas where they’re not the experts or aren’t paying enough attention. We've started with optimising bills, where we're already saving households thousands, and are now expanding into new categories. Similar to how Amazon picked books as its first category and grew from there.
We’re growing fast, and it's working. 20x YoY growth makes us one of the fastest scaling startups in the UK. And NPS of +70 (higher than Apple) shows that our users love it.
We've just launched two more novel new products (on top of our existing bill optimisation). Insurance: we're the first to get the regulatory approval and build the tech to actually do the full insurance discovery and purchase journey as an agent for the user (not just give them a link to the best deal). Subscription management: lots of companies use Open Banking to draw pretty graphs – we're the first to use it to actively save people money starting by cancelling unwanted subscriptions for them.
It would be easy to look at this and think we've got it all figured out. But we've only scratched the surface; our ambitions are SO much higher.
We’re building a new category of product which is hard, so we’ve stacked the deck in our favour: an experienced founding team with multiple exits, and investors including the founders of Monzo, Wise, Booking.com http://Booking.com, lastminute.com http://lastminute.com, Onfido, Funding Circle, Tide, Habito and more.
Still - the problems we’re solving are hard. ‘Talk is cheap’ applies to agents too. To have REAL impact, agents need to break out of the sandbox and take action in the real world where there are consequences. This means solving all the hard, thorny, interesting, frustrating problems the real world has to offer.
THE ROLE
What Nous does for members can feel simple: helping them understand their bills, save money, and avoid admin. But delivering that reliably at scale is complex. This role is about improving the systems behind the scenes, the workflows, tools, automations and processes that help us serve members well as we grow.
That’s where you come in. You’ll join the Operations team at the heart of the business — close enough to our members to understand what is really happening, and technical enough in mindset to help redesign how the operation works as we scale.
This is not a traditional customer operations role. You will spend some of your time close to the frontline, supporting members, understanding tickets and conversations, and seeing where our systems work brilliantly or fall short. That context matters. We believe the best operational systems are built by people who understand the customer experience in detail, not from a distance.
But the core of the role is helping us build the next version of operations at Nous. You’ll identify repeated work, spot failure modes, turn messy processes into clear procedures, and own automations end to end. You’ll help us move work out of inboxes and manual processes, and into better systems, workflows, tooling and AI-assisted operations.
Some days you’ll be digging into a broken process to understand the root cause. Some days you’ll be designing a better workflow, writing a clear operating procedure, or using AI and internal tools to automate work that used to be manual. Other days you’ll be working with product, engineering, data and experienced operators to improve the journeys our members go through and the systems that support them.
You do not need to arrive as a software engineer. But you do need to be unusually quick to pick up technical tools, excited by AI, and willing to get under the bonnet of how things work. You’ll be expected to learn fast, experiment intelligently, and become someone the team trusts to take a messy operational problem and turn it into something robust, repeatable and scalable.
It’s a rare chance
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