AI Systems Engineer

About the Role

Join a dynamic Manufacturing AI company based in Munich that is at the forefront of intelligent software development tailored for industrial engineering settings. As an AI Systems Engineer, you will innovate AI copilots that aid engineers in diagnosing technical issues, planning maintenance activities, navigating extensive documentation, and making quicker operational decisions.

Key Responsibilities

• Design and implement production-ready AI copilots to support manufacturing and engineering operations.
• Create agentic workflows combining Large Language Model reasoning with enterprise tools and technical datasets.
• Develop backend services and APIs utilizing Python and FastAPI frameworks.
• Establish Retrieval-Augmented Generation (RAG) pipelines to efficiently access large volumes of technical manuals, maintenance logs, and engineering documentation.
• Design architectures for vector search and knowledge retrieval tailored to complex industrial datasets.
• Integrate AI agents with internal databases, APIs, maintenance tracking systems, and operational software suites.
• Implement security measures including safeguards, permission controls, and validation protocols to ensure trustworthy AI operation in critical business environments.
• Enhance retrieval effectiveness, agent dependability, latency improvements, and accuracy of AI system responses.
• Collaborate closely with product and engineering teams to translate manufacturing workflows into practical AI functionalities.
• Contribute to shaping the overall industrial AI platform architecture within the company.

Experience and Skills Required

• Minimum of four years’ professional experience in Software Engineering, AI Engineering, Backend Development, or related disciplines.
• Proficient Python developer with strong commercial project experience.
• Expertise in building APIs and backend applications using FastAPI or equivalent frameworks.
• Practical experience designing and deploying applications powered by Large Language Models.
• Experience constructing Retrieval-Augmented Generation systems utilizing vector database technologies.
• Familiarity with agent orchestration frameworks like LangGraph.
• Solid knowledge of PostgreSQL database management and data modeling.
• Proven track record of advancing AI solutions from prototypes to scalable, reliable production-ready systems.