Devops specialist állások, munkák egyetemi végzettséggel

• AI/ML keretrendszer szoftver-infrastruktúra tervezése, kiépítése;
• Komponensek Docker konténerizációja;
• GPU-kompatibilis image-k kialakítása, AI workload-specifikus erőforráskezelés;
• CI/CD pipeline-ok tervezése, kiépítése, optimalizációja;
• AI model deployment, verziókezelés;

• Configuration Management Expert with special focus on the C++ build system with CMake
• Manage and extend the SW build system for C++ according to product development.
• Implement changes, integrate new SW components and build variants.
• Migrate components from make to CMake.

• Standardize Azure architectures and resources using Infrastructure-as-Code — with a strong focus on automation and enabling internal teams through self-service capabilities
• Develop and onboard innovative cloud-based applications as part of Roland Berger's internal digital ecosystem

• Design, implement and continuously improve DevOps concepts, CI/CD templates, pipelines and automation for SAP landscapes (e.g. SAP BTP, S/4HANA)
• Enable reliable build, test and deployment processes across SAP Cloud and on-premise environments

• You are part of a team who is responsible for the global infrastructure services (planning, design, installation and administration)
• You ensure the proper service delivery of the entitled end to end services (network infrastructure, Storage, Server, VM, interfaces, 芒聙娄)

Build enterprise cloud infrastructure that provides European data sovereignty and hyperscaler-grade capabilities. You'll work on SAP Cloud Infrastructure, solving complex distributed systems challenges at scale: multi-region networking, container orchestration, storage systems, and the APIs that...

• Enable and optimize CI/CD practices to ensure reliable, automated software delivery.
• Own and maintain development and test environments, ensuring stability, scalability, and reproducibility.
• Drive automation across build, test, deployment, and release processes.

• Operate, maintain, and further develop cloud-managed Kubernetes clusters
• Build, maintain, and continuously improve CI/CD pipelines using GitLab CI
• Develop and maintain infrastructure as code using Terraform, Ansible, and Helm
• Automate operational tasks and improve developer workflows

Architect and implement cloud-native data solutions using GCP (BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Composer, Cloud Storage) Lead the design and development of complex data pipelines and distributed processing frameworks that ensure scalability, performance, and operational reliability...

Architect the ML Platform: Design, implement, and maintain a robust MLOps infrastructure that enables researchers to move seamlessly from local experimentation to global production....

Model Onboarding & Deployment: Take AI models from internal and external users into production inference workflows. Package and deploy models as containerized inference endpoints. Define and operate validation gates covering functional checks, performance benchmarks, and safety/​security...