Engineer & Agentic Developer

For an international industrial group, we are looking for an AI Engineer to join its central Data Science & AI Engineering team. This team is part of the corporate R&D department and delivers projects for business units worldwide. The team combines specialists in agentic AI, time series, and computer vision, and works directly with scientists, process engineers, and business owners. The team runs its own agentic platform on a cloud platform 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 involves more use cases in parallel, more connected data sources, and a larger library of shared skills and tools. You will build these agents and strengthen the platform underneath them.

What you will do. Agent development.

• Design and build agents that carry complex, domain-specific logic, translating expert knowledge from scientists and engineers into reasoning steps, tools
• Build multi-step and multi-agent workflows with an orchestration framework, combining retrieval, tool calls, and business rules
• Connect agents to structured enterprise data in a data analytics platform, often combining several sources in one solution

Context and knowledge management.

• Define what context an agent needs to reason correctly: instructions, retrieved documents, table and column descriptions, domain rules
• Improve metadata on the data platform so tables and fields are described well enough for agents to use them reliably
• Design retrieval and grounding strategies that keep answers traceable to their source

Skills and tooling.

• Build reusable skills and tools that agents across use cases can share
• Decide which agent gets which tools and permissions, and keep the tool library maintainable

Evaluation and quality.

• Set up structured evaluation of agent behavior: test sets, metrics, regression checks, and human review
• Use evaluation results to improve prompts, tools, and architecture, and report quality clearly to stakeholders

Delivery and collaboration.

• Deliver solutions on a cloud platform and a data analytics platform, with IT owning integration and operations
• Contribute to platform architecture decisions and engineering standards
• Follow developments in LLMs and agent frameworks and assess what is worth adopting

What they ask

• Master's degree in Computer Science, or a PhD in Mathematics or a related quantitative field
• 3+ years of hands-on software or AI engineering, including building agentic or LLM-based systems
• At least one agentic application delivered to production that goes well beyond a chatbot or summarization tool
• Real production experience on a cloud platform and a data analytics platform
• Strong Python and solid software engineering practice: testing, version control, code review, clean architecture
• Hands-on experience with an orchestration framework or a comparable framework, and with similar models
• Experience with RAG, tool calling, and structured evaluation of LLM output
• Backend and data focus: comfortable working with data platforms, APIs, and system architecture
• Clear communication in English with technical and non-technical stakeholders

Nice to have.

• Experience in an industrial, manufacturing, chemical, or process environment
• Experience with specific cloud and data tools
• Experience building shared platforms or internal developer tooling