Senior AI Engineer

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.

• 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.