Build the back office of the future, in Europe.

What you'll do

• Manage our bare-metal server fleet end to end: provisioning, OS hardening, monitoring, capacity planning.
• Design and run deployment pipelines — every release reaches production through automation you built, not SSH-and-paste.
• Deploy and operate AI GPU servers: drivers, CUDA stack, containerised training and inference workloads.
• Own infrastructure security: network isolation, firewalls, encryption at rest and in transit, access control, patching cadence.
• Write the runbooks, so 3 a.m. problems have a documented path back to green.

What you bring

• 5+ years running production infrastructure on bare metal or dedicated servers.
• Deep Linux knowledge — networking, storage, systemd, performance debugging.
• Hands-on experience deploying GPU servers for ML workloads.
• A security-first reflex: you harden by default and can explain every open port.
• Infrastructure-as-code discipline. Ad-hoc changes make you uncomfortable.
• High capacity to work with AI tools — they are part of how we build, not a novelty.

Languages: English.

What you'll do

• Build product features across the stack: TypeScript/React on the front, typed APIs and services behind them.
• Set the bar on code quality — reviews, testing discipline, and architecture decisions that hold up a year later.
• Profile and fix performance where it matters: rendering, queries, payloads, cold starts.
• Shape the engineering culture of a small founding team. Your standards become the standards.

What you bring

• A senior track record shipping and maintaining production web applications.
• Fluency in design patterns and software architecture — and the judgement to know when not to use them.
• A code-quality orientation you can show, not just claim: tests, types, readable diffs.
• Performance instincts backed by measurement, not folklore.
• High capacity to work with AI tools — they are part of how we build, not a novelty.

Languages: English.

What you'll do

• Run continued pretraining (CPT) and supervised fine-tuning (SFT) to adapt LLMs to our domain, in Dutch, French and English.
• Build evaluation harnesses that tell us whether a model change actually helped before a customer sees it.
• Design retrieval and grounding so the agent answers from the customer’s real data, not from vibes.
• Optimise inference — quantisation, batching, serving — on our own GPU servers.

What you bring

• 5+ years in machine learning engineering, with recent hands-on LLM work.
• Practical experience with CPT, SFT, evaluation methodology, and inference serving.
• Strong Python and comfort working close to the GPU.
• A healthy scepticism of benchmark numbers and a habit of checking real outputs.
• High capacity to work with AI tools — they are part of how we build, not a novelty.

Languages: English.

What you'll do

• Own Chut’s social presence: content, cadence, and the community around it — in three languages.
• Run the sales pipeline from first touch to booked workflow audit to signed design partner.
• Talk to Belgian SME owners in their own language, literally: Flemish on Monday, French on Tuesday.
• Feed what you hear back into the product — you’re our closest ear to the market.

What you bring

• Proven experience in digital sales and social media — you can show campaigns that converted, not just impressions.
• Comfort selling to small-business owners: practical, direct, no jargon.
• Self-direction. You’ll define the playbook, not follow one.
• High capacity to work with AI tools — they are part of how we work, not a novelty.

Languages: Flemish/Dutch, French and English — all three, fluently.