As a member of the back-end team, you will contribute to the development and enhancement of cloud-native software solutions for Deloitte Tax & Legal Germany. In this entry-level role, you will focus on building Python-based back-end components that are efficient, maintainable, and aligned with best practices.We are looking for a motivated DevOps Engineer with 1-2 years of experience to join our team. The ideal candidate should have a foundational understanding of Azure cloud services, including Gen AI services, and hands-on experience with DevOps tools like Jenkins, Azure DevOps, and artifact management. This role will focus on automating deployments, managing Kubernetes clusters (AKS), and optimizing containerized applications while ensuring system reliability and security.Responsibilities:Develop and maintain CI/CD pipelines using Jenkins and Azure DevOps. Work with Azure services, including Gen AI services,Storage, Networking, and App Services. Deploy and manage containerized applications on Azure Kubernetes Service (AKS). Create, optimize, and debug Docker files for efficient containerized application deployment. Develop, maintain, and deploy applications using Helm Charts for Kubernetes. Manage artifact repositories and streamline package management workflows. Configure AKS monitoring and logging using tools like Azure Monitor, and Log Analytics workspace. Implement and manage networking in AKS, including ingress controllers, service discovery, and network policies. Troubleshoot and debug containerized applications, deployment failures, and infrastructure issues. Collaborate with development teams to enhance automation, scalability, and performance.Requirements:1-2 Years as Devops Enginee Basic knowledge of Azure cloud services, including Gen AI services, VMs, Storage, Networking, and App Services Experience with CI/CD tools like Jenkins or Azure DevOps Understanding of artifact management (Azure Artifacts, JFrog, or Nexus) Hands-on experience with Kubernetes (AKS preferred) and containerization (Docker) Experience in writing and debugging Dockerfiles Knowledge of AKS monitoring and logging tools (Azure Monitor, Prometheus, Grafana, etc.). Understanding of networking concepts related to Kubernetes and Azure. Strong scripting skills in Python. Good troubleshooting and debugging skills for containerized applications.