Software Engineer in London

Build the systems that automate parts procurement.

About Carpata: We're building the infrastructure that will power how parts are identified, bought and sold across the world. Carpata is building the AI-native operating system for B2B parts procurement, starting with the $2 trillion+ global vehicle aftermarket. Despite its scale, much of the industry still runs on phone calls, emails, WhatsApp and spreadsheets. Identifying, quoting and ordering a single part can take 15 minutes or more, while return rates can reach 20%. The result is high operating costs, complex supply chains and significant inefficiency for both the businesses buying parts and those supplying them.

At the heart of the problem is fitment: identifying exactly which part fits which vehicle. With millions of vehicle configurations, thousands of manufacturers and fragmented, often conflicting data sources, getting the right part isn't straightforward. Garages and fleets spend time searching catalogues, checking compatibility and chasing suppliers. Distributors employ large teams to handle enquiries, validate parts, prepare quotes and process returns. Even where digital systems exist, much of the work still requires manual intervention.

We believe solving fitment within the workflows businesses already use is the key to automating the entire industry. We've built a proprietary vehicle and parts intelligence platform that identifies and validates the correct components. Combined with AI agents, this enables us to automate the procurement process end to end — from enquiries over email, WhatsApp and phone through to sourcing across suppliers, ordering and invoice reconciliation. This works on both sides of the transaction: helping garages and fleets buy the right parts faster, while helping distributors handle enquiries, quotes and orders with less manual work. It connects existing supply relationships across original equipment, aftermarket and recycled parts, without requiring businesses to abandon the tools they already use. The result is faster procurement for buyers, lower costs to serve for suppliers and fewer incorrect parts moving through the supply chain.

We're growing quickly, with a significant enterprise opportunity ahead. We're already working with major vehicle manufacturers, aftermarket and recycled parts distributors, fleets and dealer groups. Our technology is live, delivering measurable results, and we're expanding its use across customer operations. For one major enterprise customer, we're automating 72% of parts identification at 99.9% accuracy, across nearly 200,000 parts every month. We have a growing pipeline of enterprise opportunities representing over £800 million in addressable annual parts transactions to pursue in 2027. Our focus is on converting that opportunity into deployments and scaling our technology across the industry. As more transactions flow through Carpata, verified outcomes help us improve the intelligence behind future part identification and automation. Automotive is just the starting point. We're starting with cars and vans, but the same challenges exist across trucks, agricultural equipment, construction machinery, plant and industrial assets. Our ambition is to build the intelligence and transaction infrastructure for parts procurement across these markets, connecting manufacturers, distributors and customers globally.

The Role: Your first project is the vehicle data that sits underneath our catalogue. It comes from several sources that describe the same vehicle in different ways, and it keeps growing: new vehicles reach UK roads all the time, and registration plates move from one car to another. You will build the systems that keep it accurate and current, automatically, across every vehicle on UK roads. It is a software engineering problem: matching records across sources, and building services that run reliably in production on AWS. It is not infrastructure-heavy: the Lambda, Postgres and Terraform foundations are already in place.

Beyond that, the work follows the roadmap. We are building in three areas: catalogue intelligence, which is identifying the right part for a given vehicle and catching errors before customers do; workflow automation, which covers search, ordering and integrations with the systems garages and dealers already use; and supply, connecting more suppliers so customers can order through us whoever they buy from. In your first year you would work across all three. That means moving between backend, data and, when needed, front-end work, and going deep where a problem calls for it. As the team grows there will be room to own one of these areas.

You would join a small team: our Lead Engineer, who owns the platform architecture and will get you up to speed; our catalogue lead, who brings the automotive knowledge; and Pete, our CTO.

The Stack: TypeScript throughout the platform, with some existing data tooling in Python. Postgres. AWS Lambda with Terraform. A GraphQL API. Next.js and React on the front end. Most of our code is written with Claude Code, and we think that changes what the job is. Writing the code is no longer the hard part. The hard part is being clear about what should be built, agreeing what done looks like before any code exists, and being able to show it works afterwards. That means time with the people who know how vehicles and parts actually work, because an agent can only be as precise as the person directing it. We are moving towards a way of working where agents take a piece of work from ticket to reviewed pull request, and people make the product decisions. It is not finished, and we want people who want to help shape it. The language you have written most in matters less than it used to, though TypeScript is home.

Why Join Now: We're a small team with paying customers, proven technology and a huge amount left to build. Our founders have built and exited automotive technology businesses before. We're backed by Concept Ventures and Nosara Capital, alongside angels from Carwow, JustPark, Auto Trader and Bumper. You would own our vehicle data: how accurate it is, the systems that keep it that way, and the call on what gets fixed next. The aim is that a garage, dealer or fleet orders the right part first time, from whichever supplier they use, without anyone checking it by hand. We're at the stage where the people joining will have a real influence on what gets built, how we work and the direction of the business. You'll work directly with the founders, take ownership of difficult technical problems and see your work used by major enterprises. This is a permanent role with equity, so the upside is yours as well as ours. We're building the technology to change how an entire industry operates, and we're looking for people who want to help make it happen.

Who We Are Looking For: A software engineer, backend or full stack, who will take on a hard problem and see it through, rather than work through tickets. You have turned a process that ran by hand into one that runs without a person in the loop. You ship small and often: pull requests merged the week they open, then improved on what breaks. You build with AI tools every day, catch them when they are wrong, and do not call something done until you can show it works. You back your decisions with numbers and share them when they are bad as well as when they are good. You have worked somewhere small, or started something yourself, and had to work out the approach rather than be handed a specification. It does not matter if it did not work out. You go for the hardest part of the problem first, not the predictable route. You build for a mechanic at 6pm on a Friday, not for a demo. Experience on data projects helps but is not essential. An interest in cars helps but is not essential either.

Who We Want To Hear From: We particularly want to hear from people under-represented in engineering. Every application is read by a person. If the process or working pattern would make it hard for you to apply, tell us and we will talk about it.

Type: Permanent, full-time, five days a week.

Salary and Equity: £70k to £90k, plus equity. Equity is part of the package for every full-time employee.

Holiday Working Pattern: Hybrid. Two days a week in our office at Elephant & Castle, the rest remote. If that does not fit your life, say so when you apply.

Start: As soon as you are available. We can work around a notice period.

Visa: We cannot sponsor visas.

Hiring Process: 45 minutes with Pete, our CTO: your background, the work you are proudest of, and what we are building. 60 minutes technical, in person, with one of our engineers. 60 minutes with Matt, our CEO. The technical stage is in person by default. If travelling in is difficult, we can run it remotely. Tell us about any adjustments you need and we will make them. We give clear feedback at each step and aim to come back within a week.