Description
No description provided.
Responsibilities
•Operate and further develop an AI-based chat and assistance 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, in production operations
•Create technical and operational documentation and architecture artifacts for the solutions
Requirements
•At least 5 years of DevOps, Platform, or Cloud Engineering experience 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 for an OpenShift-to-AWS transition within the last 4 years
•At least 3 years of experience in incident management, problem management, and production systems operations
•Must be an employed staff member of a system house, IT service provider, or similar; freelancers cannot be presented to the client and should not apply
Nice to have
•Agentic engineering, including agent orchestration, tool use, 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 technologies, engineering tools, or operating processes in AI/GenAI/agentic environments
•Technical operations, 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 and Azure AI Services
•IAM, security, and secret management in complex cloud environments
•MCP-based integrations, including production MCP servers, tool gateways, registries, and tool integrations
•Governance, security, and compliance for AI solutions, including guardrails, auditability, policy enforcement, and decision traceability
Conditions
No conditions stated in the posting.
