AI Engineer

Description

The role helps shape the company's agentic AI and data platforms as part of its digital transformation.

You take technical ownership of AI, agent and data solutions across their full lifecycle, in a supportive, team-oriented setting.

You advise stakeholders on complex technical questions and support them with technical concepts, prototypes and integration work, so that agentic AI and data solutions are assessed, built as reusable components and run reliably in enterprise environments.

Responsibilities

• Work with business departments, solution designers, IT operations and security to examine use cases, data sources, data models and integration needs.
• Design scalable, secure and production-ready architectures based on that analysis.
• Build, deploy and maintain agentic AI systems in enterprise environments, whether cloud, hybrid cloud or on-premise.
• Assess technologies, frameworks and SDKs such as OpenAI SDK, LangChain, Microsoft Agent Framework and Semantic Kernel, and use them to create reusable components.
• Connect structured and unstructured data sources to AI, agent and data platforms.
• Build reliable data pipelines covering preparation, indexing, chunking, embeddings and semantic search.
• Set up logging, tracing, metrics, alerting and performance analysis with tools such as Langfuse and OpenTelemetry.
• Apply LLMOps and MLOps practices, including CI/CD, versioning, automated evaluation, regression testing and controlled rollout and rollback.

Requirements

• A university degree, preferably in Computer Science, Business Informatics, Mathematics, Data Science, Industrial Engineering or a comparable field.
• Several years of hands-on experience delivering complex software, AI or data projects.
• Solid Python development skills and experience with agent frameworks or SDKs such as OpenAI SDK, LangChain, Microsoft Agent Framework, Semantic Kernel or similar.
• Very strong data engineering skills, especially for connecting, preparing, transforming and serving varied data sources.
• Experience with Microsoft Azure, Kubernetes, containers and cloud-native architectures.
• Experience with Langfuse, OpenTelemetry or comparable observability tools.
• A strong focus on customers and products, with attention to business value, user adoption, reuse and ongoing improvement of live agentic AI solutions.
• Confident presence, strong communication skills and enthusiasm.
• Self-driven, comfortable working in a team and flexible.
• Good written and spoken German and English.