AI Engineering Capability Owner

The role
This is a rare chance to reshape a business from the inside. You will start in development, where our AI-DLC is already running, and build on it: strengthening how engineering works with agents and making it the way the whole team works. Then you follow the thread outwards. Your job is to own capabilities, meaning end-to-end business activities such as how we reconcile funds at the end of the day or how an IT operations service is delivered. For each one, you understand the workflow, see where AI can make it work better or differently, and engineer the improvement all the way to practical use. Over time, the scope is the whole business: how we can run better, and differently, with AI. And because our platform moves money for customers every day, it has to be done safely. That is part of the fun: using AI where it counts, with the guardrails to match. This is a hands-on role for someone who loves to build. There is no people management and no evangelist hat to wear, no second AI platform or center of excellence to run and no strategy slides to produce. Your time goes where the difference is made: in the code, the specifications and the work itself. You sit in development and report to the CTO, and you have the final say on the method: how agents are used, how work is specified, how output is reviewed and how tests are written. You will work side by side with colleagues across the business, bringing them along with working results and real influence.

What you will own
The way engineering works with AI: the agent harness, shared repository and compliance-gated pipeline, improved continuously from today’s baseline. The method the team works by: how agents are used, how work is specified, how output is reviewed and how tests are written. Business capabilities: following them across teams, systems and processes, starting with areas such as reconciliation, funds management and IT operations, and engineering AI-assisted improvements all the way into daily use. Documentation and remediation: using agents to express what our platform does as specifications and tests, speed up security fixes and automate evidence for our control framework. Guardrails that let engineers build their own AI-powered tooling safely, within the group’s shared permissions model. Bringing colleagues with you: pairing with engineers and business colleagues, showing what works and following improvements through to adoption, so that people build confidence in working with agents.

Your first months
You will start where we are strongest: in development. Our AI-DLC will be measurably faster and better and in daily use across the team, with the first capabilities documented as executable specifications and tests, and control evidence generated by the pipeline. From there, your first business capability will be in your hands: mapped end to end, with AI-supported improvements delivered into the way the work is actually done. You will spend more time building than presenting. Success will be visible in concrete results: more efficient workflows, reliable outputs, stronger control evidence, more engineers working with agents daily on real work, and colleagues across the business who adopt what you build and ask for more.

What you will bring
You are a senior engineer who still writes code most days and has changed how you work because of coding agents, not just added them to the toolbar. Your career includes at least one long stretch inside a production platform that handled money or other regulated data. Eight or more years in software engineering, five or more of them in backend or platform engineering on production systems, with fluency in at least one of Python, Go, Java or TypeScript. You have modernised something old while it stayed live, whether monolith to services, on-premise to cloud or a language or runtime migration, and you can tell us what you documented first, what you tested first and what went wrong. Two or more years building LLM-based systems that reached production, with ownership of context and prompt design rather than just API calls, plus an evaluation framework with test sets, pass criteria and regression tracking that you used to decide whether something shipped. Twelve or more months using coding agents such as Claude Code, Copilot, Cursor or Codex on real work, with a clear view of delegation boundaries, review discipline and failure cases. Hands-on CI/CD, automated testing and release gating, including a pipeline you made enforce something rather than merely report it. Experience from a regulated environment with enforced access control, audit logging, change evidence and segregation of duties, including producing or defending evidence for an audit or certification such as ISAE 3402, SOC 2, ISO 27001 or PCI DSS. Specifications that other engineers built from and test suites that others relied on, plus the ability to understand business workflows, talk with non-technical colleagues and win cooperation across teams without line-management authority.

Lead from the code
You are a builder who sets direction and brings people with you. You define the method, make the case for it and have the conviction to see it through, without waiting for permission or a title. You win people over with proof rather than slides: a working demo, a spec that holds up, a test suite that catches a real bug. When the team pushes back, you listen, adapt the how and hold the line on the why. You are confident without being loud, honest about what you do not know, and respectful of the people and platform that keep the money moving.

Why you will love it here
Inpay Group is growing, and this role puts you at the centre of that journey. Here is what you can look forward to: A role that is genuinely new: take AI-native engineering out of the development team and into the whole business, and define how it is done. Real reach: from how engineering works with AI to how a whole payments business runs, with your work live on a platform that moves real money. A flying start: our AI-DLC is already running and agents already write our tests, so you build on real momentum instead of starting from zero. A direct line to the CTO, the final say on method and a genuine say in where technology goes next. An open, informal culture where everyone is heard and good ideas win, with a fun office in the heart of Copenhagen, right next to Amalienborg, or remote within our working time zone. We are aiming for a start in January 2027, or earlier if your notice allows. You will be employed by Framm ApS, part of Inpay Group.

Interested
If you want to be the one who shows how a payments business can work differently with AI, we would like to hear from you. Click Apply below and upload your CV and application.