
Senior AI Engineer
- Remote, Hybrid
- Rotterdam, Netherlands
- Amsterdam, Netherlands
- The Hague, Netherlands
- Utrecht, Netherlands
+3 more- €81,000 - €91,000 per year
- Products & Labs
You take AI from demo to production and own it end to end — when it breaks, you fix it. Strong execution, real ownership.
Job description
Maybe you call yourself an AI Engineer, an LLM wrangler, a "does it actually work outside the demo" specialist… or maybe you just call yourself Alex. Whatever you call yourself: you'll build and ship the AI that All Your BI puts in front of real clients, and own it end to end. Not demos. Production systems that survive contact with real clients — and when something breaks, you're the one who fixes it.
What you get
A salary between €81,000-€91,000 including holiday allowance, based on your experience.
€5,000 a year for your own growth, with a real say in how you spend it.
25 vacation days + the option to buy up to 10 more + local public holidays + the option of a sabbatical up to 4 months.
Two trips abroad a year with the whole team + occasional drinks and team outings.
€500 home-office budget and a great laptop.
A well-earned "Hey, well done Buddy!", so now and then.
Hybrid in the Netherlands: flexibility to work from home with office visits and occasional client meetings.
Benefits across the EU: the perks above are AYBI's and go to everyone, everywhere. Statutory benefits (pension, health, social security, leave, sick pay, notice) follow the hire's country via their local contract or EOR.
About us
All Your BI is a remote-first data agency based in Rotterdam. Since 2019 we've grown from a boutique consultancy into an international data team of more than 60 data heroes spread across Europe. We deliver managed BI services for logistics and industrial companies, helping reduce data waste and move businesses forward. We live for the WOW moment, that sparkle in users' eyes when they gain new insights and discover opportunities. We work according to Holacracy: little hierarchy, lots of ownership. Serious work. Serious fun.
What the job looks like
Build and ship the AI behind our products and client solutions: LLM applications, RAG over messy real-world data, agents and tool-calling. You take these from demo-grade to production-grade.
Own production end to end: when something breaks, you're the one who fixes it. You implement evals, observability and tracing, and guardrails against hallucination and prompt injection, so problems surface fast and get resolved faster.
Keep AI affordable: track cost and latency per task, and use caching, routing, and the right model for the job rather than the biggest one.
Work within the architectural guidelines set by our Lead AI Engineer, and flag early when something in that direction isn't holding up in practice.
Translate AI capability into real client value and push back on anything that's AI for AI's sake.
Job requirements
What you bring
Attitude and execution: energy, curiosity, and a strong bias to fix things yourself. When something breaks in production, you dig in and resolve it, you don't wait for direction. You can be trusted to own a production system without close supervision.
AI/ML engineering, in production: you've built and shipped LLM/GenAI systems that real people use, RAG, agents, tool-calling, not notebooks and demos. Strong Python, and you know the modern AI stack (LLM APIs across providers like Anthropic / OpenAI / open models, vector databases, an orchestration framework) well enough to know where it breaks.
Reliability & LLMOps: you make AI dependable, evals, observability and tracing, guardrails, prompt and version control, cost and latency budgets.
Client & business sense: you can tell AI that creates client value from AI that's just hype and explain which is which to a non-technical client, in strong English.
Nice to have: data or BI background or consultancy experience; cloud + deployment muscle (AWS / Azure / GCP, Docker, CI/CD); model distillation, structured outputs, and multimodal pipelines.
We're a growing team across Europe, and we hire to widen that mix, not narrow it. What matters is what you can do and the perspective you bring, not your age, gender, ethnicity, orientation, disability, background, or where you studied. If the role excites you and you bring most of it, apply: the people who add the most rarely tick every box.
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