devops engineer for AI platforms

Randstad Deutschland provides human resources services.

• Operate and further develop an AI-based chat and assistant system, including GenAI and agent components, in production;
• Build, configure, and operate CI/CD pipelines, deployment processes, and automated operations for AI and cloud applications;
• Operate, secure, and optimize containerized runtime environments based on Kubernetes and comparable cloud-native platforms;
• Implement, integrate, and operate MCP servers and MCP-based connections for agent and tool integrations;
• Ensure the availability, scalability, stability, and performance of production systems;
• Integrate and operationalize GenAI services and agentic-engineering tools, such as AWS Bedrock, Azure AI Services, and AWS Kiro, within production operations;
• Create technical documentation, operational documentation, and architecture artifacts for developed and operated solutions.

• At least 5 years of experience in DevOps, platform, or cloud engineering with operational responsibility for production systems;
• At least 3 years of experience building and operating CI/CD pipelines and automated deployment processes;
• At least 1 year of experience operating and further developing AI, GenAI, or agentic applications;
• At least 3 years of experience in cloud and container platform operations supporting the transition from OpenShift to AWS within the last 4 years;
• At least 3 years of experience in incident management, problem management, and production IT operations;
• Nice to have: experience in agentic engineering, including agent orchestration, tool usage, multi-agent architectures, and agent lifecycle management; production-ready operating models, runbooks, support structures, on-call and escalation processes; scaling, high availability, resilience, and performance optimization of production cloud-native platforms; introducing new technologies, engineering tools, or operational processes in AI, GenAI, or agentic environments; technical operational, architecture, and decision documentation for production platforms and AI systems; collaboration with architecture, platform, security, development, and operations teams in complex organizations; GenAI platforms and AI foundation services such as AWS Bedrock or Azure AI Services; IAM, security, and secret-management concepts in complex cloud environments beyond the minimum requirements; MCP-based integration scenarios, including production MCP servers, tool gateways, registries, or tool integrations; governance, security, and compliance requirements for AI solutions, including guardrails, auditability, policy enforcement, and decision traceability;
• Freelance candidates are not suitable for this project.

• The project accepts applications exclusively from employed staff of system houses, IT service providers, and similar companies.