GEN AI Engineer

At Xccelerated, we place engineers where they can have real impact and this one is about as high-impact as it gets.

A large Dutch financial institution is rethinking software delivery from the ground up. The goal: roll out AI agents and GenAI tooling across a massive engineering organisation and change how software actually gets made, not just in theory, but in practice, at scale. You’ll join this transformation as an Xccelerated engineer, embedded in a newly formed hub that sits at the centre of it all, for at least the first year.

This isn’t an AI enthusiast role. It’s an engineering role for someone who happens to be obsessed with AI. We’re looking for engineers with 3-6 years of experience who live and breathe this space. People who follow the latest model releases, experiment constantly, have opinions on agentic architectures, and can’t stop building things. If you’ve been tinkering with LLM tooling, coding agents, or AI-assisted workflows in your own time, we want to talk.

What you’ll actually do

You’ll be part of a newly formed hub built to accelerate the software delivery lifecycle through AI. Think greenfield, you’re not walking into a legacy team maintaining old infrastructure. You’re helping define what modern software engineering looks like inside a major financial institution.

In practice, that means:

• Designing and building AI-powered agents that improve how engineers write, test, review, and ship code
• Turning GenAI experiments and prototypes into robust, reusable building blocks that teams across the organisation can adopt
• Embedding agentic capabilities directly into existing engineering tools and workflows
• Defining standards for agent design, system integration, and developer experience
• Helping teams measure the actual impact of AI tooling on software delivery
• Coaching and mentoring engineers on how to work effectively with GenAI and coding agents day-to-day

Do you have experience in DevOps?, Do you have a Master’s degree?, 3-6 years of experience in a technical role; software engineering, DevOps, cloud, ML engineering, or data science. What matters more than the title is whether you’ve shipped real things end-to-end and understand the full software delivery lifecycle., * Is genuinely passionate about AI. You follow the space closely, have strong opinions, and are constantly experimenting

• Has used coding agents and agentic tools in practice (in production, on side projects, in hobby builds, it all counts)
• Builds across languages, tools, and stacks comfortably. You solve the problem with whatever fits best
• Has experience with cloud platforms and solid engineering fundamentals: testing, deployment, observability, infrastructure as code
• Can go from ambiguous idea to working software without needing a perfect brief
• Communicates technical concepts clearly to both engineers and non-technical stakeholders
• Thrives in ambiguity, adapts fast, and finishes what they start