AI Engineer

pOn behalf of our client, an international industrial group, we are looking for an AI Engineer to join its central Data Science AI Engineering team. The team is part of corporate RD and delivers projects for business units worldwide. It combines specialists in agentic AI, time series and computer vision, and works directly with scientists, process engineers and business owners. /ppThe team runs its own agentic platform on Azure with a custom agent harness. It already supports several use cases in production, from finance processes to research assistants that query scientific and operational databases. The next phase is underway: more use cases in parallel, more data sources connected, and a larger library of shared skills and tools. You will build those agents and strengthen the platform underneath them. /ph3WHAT YOU WILL DO /h3h3Agent development /h3ulliDesign and build agents that carry complex, domain-specific logic, translating expert knowledge from scientists and engineers into reasoning steps, tools and guardrails /liliBuild multi-step and multi-agent workflows with LangGraph, combining retrieval, tool calls and business rules /liliConnect agents to structured enterprise data in Databricks, often combining several sources in one solution /li /ulh3Context and knowledge management /h3ulliDefine what context an agent needs to reason correctly: instructions, retrieved documents, table and column descriptions, domain rules /liliImprove metadata on the data platform so tables and fields are described well enough for agents to use them reliably /liliDesign retrieval and grounding strategies that keep answers traceable to their source /li /ulh3Skills and tooling /h3ulliBuild reusable skills and tools that agents across use cases can share /liliDecide which agent gets which tools and permissions, and keep the tool library maintainable /li /ulh3Evaluation and quality /h3ulliSet up structured evaluation of agent behaviour: test sets, metrics, regression checks and human review /liliUse evaluation results to improve prompts, tools and architecture, and report quality clearly to stakeholders /li /ulh3Delivery and collaboration /h3ulliDeliver solutions on Azure and Databricks, with IT owning integration and operations /liliContribute to platform architecture decisions and engineering standards /liliFollow developments in LLMs and agent frameworks and assess what is worth adopting /li /ululliMaster's degree in Computer Science, or a PhD in Mathematics or a related quantitative field /lili3+ years of hands-on software or AI engineering, including building agentic or LLM-based systems /liliAt least one agentic application delivered to production that goes well beyond a chatbot or summarisation tool /liliReal production experience on Azure and Databricks /liliStrong Python and solid software engineering practice: testing, version control, code review, clean architecture /liliHands-on experience with LangGraph or a comparable orchestration framework, and with OpenAI or similar models /liliExperience with RAG, tool calling and structured evaluation of LLM output /liliBackend and data focus: you are comfortable working with data platforms, APIs and system architecture /liliClear communication in English with technical and non-technical stakeholders /li /ulh3Nice to have: /h3ulliExperience in an industrial, manufacturing, chemical or process environment /liliAzure OpenAI, MLflow, Unity Catalog
- Experience building shared platforms or internal developer tooling /li /ulh3What you get: /h3ulliComplex, company-specific problems with access to real industrial data /liliRoom to explore and build, without operational load: once a solution is built, IT takes over operations /liliA multidisciplinary team where you learn from colleagues in vision AI, time series and process modelling /liliInvolvement in research projects with external partners /li /ulpLocation: Olen, hybrid (3 days per week on site) /ppLanguage: English /ppExperience: 3+ years /ppStart: as soon as possible, 6 month contract /p