MLOps Engineer – AI Platform / DevOps – 16809

Assignment Description: We are looking for an experienced MLOps Engineer

What You Will Work On:

• Establish CI/CD pipelines for AI services (build, test, security checks, deployment)
• Standardize release processes and version management for configurations and artifacts
• Ensure traceability between releases and deployed components
• Design and implement deployment patterns in containerized environments (Kubernetes/OpenShift)
• Define and manage environments (dev/test/prod) with repeatable deployments
• Support production deployments, including rollback and recovery strategies
• Implement observability (logging, metrics, tracing, alerts, dashboards)
• Create runbooks, incident processes, and troubleshooting workflows
• Perform root cause analysis and drive continuous improvements
• Implement security controls (RBAC, secrets management, logging, network policies)
• Ensure compliance with data protection and information security requirements
• Support onboarding of new AI use cases with standardized templates and documentation
• Manage LLM/RAG lifecycle (models, embeddings, vector databases, versioning)
• Establish evaluation frameworks (LLM evals, regression testing, monitoring quality & cost)
• Maintain model/artifact registry and promotion processes across environments
• Conduct knowledge transfer to internal DevOps/platform teams

What You Bring:

• Strong experience in MLOps, DevOps, or AI platform engineering
• Experience with CI/CD pipeline design and automation
• Hands-on experience with Kubernetes/OpenShift
• Experience with observability and monitoring solutions
• Strong understanding of security and compliance in cloud/AI environments
• Experience working with AI/ML systems in production
• Ability to structure and standardize processes in complex environments

If this sounds interesting, please send your CV to