You take AI from prototype to production. On data you can trust. Most AI projects don’t fail on the model, but on the data underneath. At Beeminds, that data is already in order. With the Intelligenthive\u00ae, our AI data platform on Microsoft Fabric, we build a reliable data foundation within weeks for organisations such as UNICEF Netherlands, SportCity, Swinkels and Samenwerkende Kinderopvang. On top of it, you build the AI applications people use every day: agents, assistants and automated workflows.<\/p>\n
In this role you work on both our product and client implementations, with a small team of data engineers, data consultants and architects, for several clients at once. This isn’t a solo secondment: you build on and with our own product. You keep up with the latest in AI, go to events and turn what you learn into reusable building blocks in our platform.<\/p>\n
As an AI Engineer, you’re the link between the data in the Intelligenthive\u00ae and the work people do with it every day. You build AI agents and multi-agent workflows that answer questions, carry out tasks and prepare decisions, based on the data in the Intelligenthive\u00ae. You design RAG solutions on structured and unstructured data: semantic models, documents and source systems such as SAP. You work in Azure AI Foundry and with Azure OpenAI, and for each question you pick the model that fits best on quality, speed and cost. Before anything goes live, you set up evaluation with test sets, metrics and monitoring: you know how good your agent is, and you can show it. You take solutions to production with Git, CI\/CD and containers, keep them running and take care of the essentials: access rights, logging, cost control and the requirements of the GDPR and the EU AI Act. You build reusable components into our product, so the next client goes live faster. You sit at the table with the client yourself: you ask which work should disappear, and you say so when AI isn’t the answer.<\/p>\n