Job Description

Join our Roland Berger AI Lab to design, automate, and operate secure cloud infrastructure for (Gen)AI applications. You will build CI/CD and IaC foundations, implement observability and incident response. Working closely with Architects and Backend teams, you will productionize agentic/LLM services, enable safe model fine-tuning pipelines, and uphold service readiness with SLOs, cost controls, and performance guardrails. Expect hands-on delivery in Azure, AWS and GCP, working from PoV to scaled rollout.

What you'll do

•   Build and operate the cloud platform powering Roland Berger's AI and GenAI solutions
•   Design secure, scalable, and automated cloud infrastructure with a focus on Azure
•   Establish platform standards for automation, governance, security, reliability, and cost management
•   Enable and operate AI workloads, including LLM applications, agentic systems, and machine learning services
•   Drive observability, operational excellence, and enterprise-grade service reliability
•   Collaborate with architects and engineers to turn innovative AI solutions into production-ready products

Qualifications

Degree in Computer Science/Engineering, or equivalent experience
4+ years of work experience in DevOps/SRE on Azure, AWS or GCP • Deep expertise in Microsoft Azure and familiarity with Google Cloud Platform
Strong experience with cloud automation, CI/CD, GitOps, and Infrastructure as Code (e.g. Terraform)
Proven track record operating Kubernetes, containers, networking, and secure production environments
Experience with observability, reliability engineering, incident management, and cloud operations
Familiarity with AI/ML, MLOps, LLMOps, or GenAI platforms and workloads
Ability to drive technical initiatives, influence architecture decisions, and mentor engineers
Excellent communication skills in English

DevOps Engineer (all genders)

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