Our audits aim to find where time gets lost, and how AI can be used as a tool to improve the company's operational efficiency. The client walks away with a roadmap and some initial AI tools setup, so they see a real change rather than a slide deck. After that, we embed ourselves within the team and dynamically deliver the rest of the roadmap.

This role encompasses the whole engagement. You'd start working next to a senior lead (either the CEO or CTO), learn how we do it, then take on engagements and clients of your own and begin to scope, build, and own communication with a client.

What the work looks like

• You're inside a range of businesses talking to people, from leadership down to the teams doing the work, finding out and looking for ways AI can reliably solve bottlenecks.
• You work out which tasks AI can genuinely help with, and you say so plainly when it can't.
• You turn that into a plan: what to change first, what to leave alone.
• You build it. That means wiring up data sources, AI platforms, integrations and config into their real systems and getting something live quickly.
• You agree up front what success looks like, whether that's time saved or just the worst of the grind gone, then show you hit it.
• You train the people who'll use it and ensure they properly adopt these new tools, so they keep using it after you've gone.
• You find the next workflow worth doing and continuing supporting the client.

The stack

You'll work across whatever the client already runs. That usually means one of the major clouds (AWS, Azure or GCP), the main model providers (OpenAI, Anthropic, Google, or open-weight models where data has to stay on-prem), wired into the client's existing systems through APIs, MCP servers and connectors. We don't push for a specific house stack. The job is fitting AI into their reality, including the cases where that means a sovereign or on-premise deployment.

This role requires strong technical fluency across a range of stacks, you need to be able to learn new tools, frameworks or sector specific knowledge on the fly and apply it to real work tasks being done by their team.

Working here

We're a team of four with a lot of room to own things. You'll scope the work, build it, explain it to a room that isn't sold yet, and stand behind what you ship. Every client is a different business of a different size, different sector and with different but comparable problems. You'll own those relationships and have a real say in how we run the company. It's demanding, but you get to watch a team's day get better because of something you made and build strong relationships across a range of medium to large companies.

What you'll need

• You build things, not just advise on them. That can mean setting up enterprise AI platforms, writing MCP servers and connectors, setting up skills and autonomous agents, or full applications should the client need it.
• You must have strong full stack coding experience pre-LLMs. We need someone who can build and understand the tech themselves. We strongly encourage and insist in most cases in using AI coding tools like Claude Code, but we need them to be steered by someone with strong software development.
• You know applied AI properly: what current models and tooling can and can't do, what's just marketing, and how to tell whether something actually helps the people using it. From real work, not just reading about it.
• You learn fast and want to grow. This role starts alongside a senior lead and grows into owning clients, so we care about how quickly you pick things up.
• Experience in a delivery-focused area: consulting, solutions engineering, technical pre-sales, or implementation.
• You can stand in front of a room, speak clearly and confidently, and lay out a new way of working clearly, and train a department until they're confident with it. Clients need to trust you and enjoy working with you.
• You must be able to travel into central Cambridge where our office is located.

The mindset we are looking for

• You care whether the implementation gets used. A clever build nobody touches is a failure to deliver what OpenKit strives for, and you judge your own work by whether a real team's day improved.
• You can run yourself. Being embedded means nobody's watching your calendar, and you don't need them to.

Nice to have

• You've helped a team actually change how they work, rather than handing over a tool and leaving.
• Experience deploying into regulated or security-conscious settings like public sector, finance or healthcare.
• Hands-on experience with one of the major clouds and its AI services.
• Familiarity with RAG, agent frameworks and the current applied-AI tooling.
• A second language. We work across Europe, so French in particular is useful, though not required.

Salary

£65,000 base
A performance bonus tied to client retention, renewing, and using what you built
Equity options as the company grows
A budget for training and conferences, and flexibility in how you work

How to apply

Email jobs@openkit.co.uk with your CV and a short cover letter, three paragraphs at most, on why you're a good fit. Use the subject line "FDE application – [your name]". Include either a summary of relevant experience and what you accomplished or one thing you've built that you're proud of, with a couple of lines on what it is and what you actually did on it.