AI & Data Engineer – Dusseldorf

AI Adoption, Agents & Governance Help us turn AI from potential into everyday impact. AI is changing how organizations work but technology alone does not create transformation. People do. At Advantech Europe, we are accelerating the adoption of AI across our organization. We want to empower colleagues in different business domains to transform their expertise, ideas and everyday challenges into intelligent solutions that improve how we work.

To help us make that happen, we are looking for an AI & Data Engineer who combines strong engineering capabilities with curiosity, pragmatism and the ability to work with people. You will work at the intersection of Generative AI, AI Agents, Machine Learning, Data Engineering and AI Governance. You will help build the technical foundations for responsible AI while working directly with colleagues across Advantech Europe to turn valuable use cases into production-ready solutions.

You will be one of the key technical enablers of our AI transformation.

Your mission is to accelerate responsible AI adoption across Advantech Europe from idea to production. You will work closely with the Head of AI & Digital Transformation, IT, business stakeholders and domain experts across Europe. Your responsibilities will span five interconnected areas:

• Accelerate AI Adoption: Identify and develop high-value AI and GenAI use cases across business functions, rapidly prototype ideas and help colleagues understand where AI genuinely adds value.
• Enable our AI-Agent Contributor Community: Act as a technical coach and partner for domain users developing their own AI agents. Help colleagues translate business problems into agent workflows, select appropriate tools and data sources, design prompts and knowledge retrieval, connect agents with enterprise systems, test solutions and move successful agents safely into production.
• Engineer AI and Agent Solutions: Design and develop GenAI applications, copilots and AI agents using LLMs, RAG, APIs, enterprise data and orchestration frameworks. Build agent workflows capable of securely interacting with tools, APIs and business systems, and establish reusable engineering patterns rather than isolated proofs of concept.
• Build Trusted Data Foundations: Design data pipelines and integrations that make enterprise data usable for AI and analytics. Work across structured and unstructured data, APIs, databases, documents and cloud services. Improve data quality, metadata, lineage, accessibility and observability so AI solutions are grounded in reliable information.
• Help Build our AI Governance Platform: Translate responsible-AI principles into practical technology. Contribute to an enterprise governance architecture covering the lifecycle of AI models and agents including identity and access, data governance, tool management, logging, auditing and lifecycle management. Help implement controls aligned with GDPR, the EU AI Act, security requirements and relevant industry standards.

You are an engineer who enjoys building but you are equally interested in understanding why something should be built and how people will actually use it. You enjoy working with domain experts, translating business challenges into technical solutions and making complex AI concepts understandable to colleagues who may not have a technical background. Ideally, you bring experience in several of the following areas:

• Generative AI & Agent Engineering: LLM applications, RAG, prompt engineering, agent orchestration, enterprise copilots, agent-to-tool integration, APIs, MCP or similar protocols, multi-step workflows, human-in-the-loop patterns and agent lifecycle management.
• Machine Learning: Practical experience developing, evaluating and deploying ML models, with an understanding of MLOps and model lifecycle practices.
• Data Engineering: Python and SQL, ETL/ELT, APIs, data pipelines, structured and unstructured data, cloud data platforms and modern data architectures.
• Cloud & Microsoft Ecosystem: Experience with Azure and ideally technologies such as Azure AI, Azure OpenAI, Microsoft Fabric, Power Platform, Copilot Studio, Microsoft 365, Entra /or Microsoft Purview would be an advantage.
• Engineering Fundamentals: Familiarity with modern software engineering practices such as Git, APIs, testing, CI/CD, deployment, monitoring and secure application development.
  You don't need to be an expert in everything above. We value strong engineering fundamentals, curiosity, learning ability and…