AI Engineer
Zeiss Group Open · verified Nov 1, 2026 At a glance
Mid-level AI Engineering role at Zeiss Group. Budapest · full-time.
Pay not stated AI Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Assess business use cases, data models and system connections, then shape secure architectures ready for production
- Build and operate agent-based AI across cloud, hybrid and on-premise environments, from initial design through ongoing deployment
- Select frameworks and SDKs, then turn suitable options into reusable AI components
- Connect structured and unstructured sources, preparing data pipelines, embeddings and semantic search
- Apply delivery and monitoring practices such as automated testing, tracing, metrics and controlled releases
What you bring
- A university qualification in a relevant discipline, such as computer science, mathematics or a comparable field
- Several years delivering complex software, AI or data projects, with practical Python development experience
- Strong data-engineering skills and experience with Azure, Kubernetes, containers and cloud-native systems
- Familiarity with agent frameworks and observability tools, including LangChain or another listed option
- Good spoken and written German and English
Who this fits
This role suits an engineer who can connect business needs with production-ready AI and data systems, and who values reuse, user adoption and ongoing improvement. You’ll work with teams across business, solution design, IT operations and security. The position is hybrid in Budapest.
From the employer
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.
Your ZEISS Recruiting Team:
Wenner Lili
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