AI Systems Engineer

AI Systems Engineer

Munich, Germany — Hybrid

Manufacturing AI | Industrial Software | Intelligent Automation | Industry 4.0

Our client, a growing Manufacturing AI company based in Munich, is building intelligent software designed specifically for industrial engineering environments.

They're looking for an AI Systems Engineer to develop production AI copilots that help engineers diagnose technical problems, plan maintenance, access complex documentation, and make faster operational decisions.

You'll be developing AI systems that connect LLMs with real industrial knowledge, engineering data, enterprise systems, and operational workflows.

What You'll Be Working On

• Designing and developing production-grade AI copilots for manufacturing and engineering teams

• Building agentic workflows that combine LLM reasoning with enterprise tools and technical data

• Developing backend services and APIs using Python and FastAPI

• Creating RAG pipelines capable of retrieving information from large collections of technical manuals, maintenance records, and engineering documentation

• Designing vector search and knowledge retrieval architectures for complex industrial datasets

• Connecting AI agents with internal databases, APIs, maintenance systems, and operational software

• Building safeguards, permissions, and validation mechanisms for AI systems operating in business-critical environments

• Improving retrieval quality, agent reliability, latency, and response accuracy

• Working directly with product and engineering teams to translate real manufacturing workflows into practical AI capabilities

• Helping shape the architecture of the company's broader industrial AI platform

Experience Required

• 4+ years of experience in Software Engineering, AI Engineering, Backend Engineering, or a related field

• Excellent commercial Python development experience

• Strong experience building APIs and backend applications with FastAPI or similar frameworks

• Hands-on experience developing applications powered by Large Language Models

• Experience building RAG systems using vector databases

• Understanding of agent orchestration frameworks such as LangGraph

• Strong PostgreSQL and data modelling knowledge

• Experience taking AI applications beyond prototypes and into reliable production environments