• Design, operation, and continuous enhancement of infrastructures based on VMs as well as Kubernetes/OpenShift • Work with private and public cloud platforms (e.g., AWS, Azure, or GCP) • Implementation of CI/CD pipelines and GitOps processes • Monitoring of environments including automated alerting • Technical consulting and collaboration with our clients

• Driving Germany’s digital transformation with a focus on secure, scalable and future-proof cloud platforms. • Actively working in project teams for clients across various industries. • Analyzing customer requirements and deriving viable technical solution approaches. • Designing, building and further developing modern cloud and platform architectures with a focus on Kubernetes in a private-cloud context, as well as with selected public cloud providers (e.g., AWS, Azure, GCP, STACKIT, IONOS). • Architecting and designing scalable, secure and maintainable system landscapes. • Building and operating container platforms with Docker and Kubernetes. • Automating CI/CD pipelines for builds, testing and release cycles, e.g., with GitLab, ArgoCD or Azure DevOps. • Designing and implementing infrastructure using Infrastructure as Code (e.g., Terraform, Ansible). • Evaluating existing architectures and presenting recommendations for action. • Coaching team members on cloud and platform topics. • Contributing to internal ARES projects.

• Join our team as a Senior DevOps Engineer, focusing on building scalable infrastructure for AI products. • Design, build, and maintain core cloud infrastructure using Infrastructure as Code (IaC). • Drive SRE best practices across the engineering team, defining SLOs/SLIs and promoting reliability. • Develop and manage CI/CD pipelines to automate application releases. • Build and manage a monitoring, logging, and alerting stack for system health insights.

• Data Architecture and Strategy: Lead the technical design of database topologies, ensuring high availability (HA), replication and disaster recovery are native to all solutions. • Database as a Service (Self-Service): Build automations and standards that allow developers to provision and manage databases securely and autonomously, reducing operational bottlenecks. • Performance Tuning and Optimization: Go beyond basic monitoring by performing deep query analysis (Explain Plan), tuning engine parameters and managing indexes to guarantee minimal latency. • Data Lifecycle Management: Manage backup, retention, archiving and data purging policies, balancing historical needs with cost efficiency (FinOps). • Data Incident Management: Serve as the focal point during database performance or availability crises, leading disaster recovery and conducting technical post-mortems. • Security and Compliance: Ensure protection of sensitive data through encryption (at rest and in transit), data masking and strict access/privilege management. • Mentorship and Data Culture: Promote best practices in data modeling and access patterns across engineering teams to raise the company's development maturity.