Cloud Engineer AI Workplace

KfW uses cloud technologies to build applications with artificial intelligence. The vision of the interdisciplinary team is to pave KfW's way to becoming a digital promotional bank through new technologies and innovative methods in AI and data science. Azure Machine Learning serves as the central data science workplace for developing and testing AI solutions within KfW.

• Technical further development of the existing data science workplace based on Azure Platform as a Service (Azure ML)
• Integration and operation of relevant Azure services, for example Azure Machine Learning, Azure Storage, Azure Key Vault, Azure Container Registry, network components and monitoring
• Evaluation, validation and integration of the latest Azure ML features into the platform, for example for Agentic AI, MLOps workflows
• Analysis and resolution of technical faults and continuous optimization of stability, cost, performance and degree of automation
• Implementation of security, compliance and governance requirements together with the responsible teams
• Innovation work at KfW: understanding digitalization as a driver of change and actively advancing it together with KfW

• Completed IT degree or comparable qualification
• Experience operating and further developing cloud platforms on Microsoft Azure
• Very good knowledge of Infrastructure as Code, especially Terraform
• Practical experience with CI/CD and version control, for example Azure DevOps or GitHub
• Knowledge of Azure network, identity and security concepts, for example Microsoft Entra ID, Private Endpoints, Managed Identities and Key Vault
• Ideally experience with Azure Machine Learning, MLOps, container technologies
• Structured, solution-oriented way of working and enjoyment of collaboration in interdisciplinary teams, desire to change and shape things
• Fluent German and good English
• Strong analytical and conceptual skills, goal orientation and very good communication skills