Responsibilities Independently develop, deploy, and operate scalable cloud architectures Work closely with internal teams and clients to integrate generative AI models into production cloud solutions Optimize cloud resources for performance, cost, scalability, and security Analyze and sustainably resolve complex infrastructure and performance issues Build, enhance, and automate CI/CD pipelines for cloud services and AI models Provide technical consultancy to clients and actively contribute to architectural decisions Continuously refine and advance best practices in cloud engineering and generative AI Requirements Degree in Computer Science, Business Informatics, Engineering, or a comparable qualification Several years of practical experience as a Cloud Engineer, ideally with a focus on generative AI or data-driven platforms Solid experience with at least one major cloud platform (AWS, Azure, or Google Cloud) in production environments Strong knowledge of containerization and orchestration (Docker, Kubernetes) Hands‑on experience building and operating MLOps pipelines and managing the full AI model lifecycle Solid knowledge of data engineering, data pipelines, and ETL processes Experience with modern AI frameworks and tools such as Hugging Face, LangChain, or comparable technologies Ability to analyze complex technical challenges in a structured way and implement sustainable solutions Strong communication skills, including coordination with clients and stakeholders Team‑player mindset and experience working in interdisciplinary project teams Business‑fluent German and English Willingness to travel within the DACH region #J-18808-Ljbffr
