Ai engineer

Your Role

You will play a crucial role in shaping the future of Agentic AI and Data platforms and actively contribute to the success of the digital transformation at ZEISS. In this challenging function, you will take technical responsibility for modern AI, agent, and data solutions across their entire lifecycle. As an AI Engineer at ZEISS, you work in a supportive, team-oriented environment, analyzing use cases, data sources, data models, and integration requirements together with business departments, solution designers, IT operations, and security to develop scalable, secure, and production-ready architectures.

You will help stakeholders with complex technical questions as well as with the technical concept, prototypical implementation, and integration, ensuring Agentic AI and data solutions are evaluated, developed as reusable components, and deployed reliably and sustainably in enterprise environments.

The role of AI Engineer will involve:

• Analyse use cases, data sources, data models, and integration requirements to design scalable, secure, and production-ready architectures.
• Develop, deploy, and sustainably establish Agentic AI systems in enterprise environments (cloud, hybrid-cloud, and on-premise).
• Evaluate suitable technologies, frameworks, and SDKs (e.g., OpenAI SDK, LangChain, Microsoft Agent Framework, Semantic Kernel) to build reusable components and solutions.
• Integrate structured and unstructured data sources into AI, agent, and data platforms.
• Design and implement robust data pipelines, data preparation, indexing, chunking, embeddings, and semantic search.
• Implement logging, tracing, metrics, alerting, and performance analyses (e.g., using Langfuse, OpenTelemetry).
• Apply LLMOps and MLOps practices, including CI/CD, versioning, automated evaluation, regression testing, and controlled rollout/rollback strategies.

University degree, preferably Computer Science, Business Informatics, Mathematics, Data Science, Industrial Engineering, or a comparable field of study. Several years of practical experience in implementing complex software, AI, or data projects. Knowledge of Python development and agent frameworks/SDKs such as OpenAI SDK, LangChain, Microsoft Agent Framework, Semantic Kernel, or comparable technologies. Very good knowledge of data engineering, particularly in connecting, preparing, transforming, and serving various data sources. Experience in Microsoft Azure, Kubernetes, containers, and cloud-native architectures. Experience with Langfuse, OpenTelemetry, or comparable observability technologies. Strong customer and product focus with an emphasis on business value, user adoption, reusability, and continuous improvement of productive agentic AI solutions. Confident appearance, strong communication skills, and enthusiasm. High degree of self-initiative, ability to work in a team, and flexibility. Good written and spoken German and English skills.