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 cv@veritaz.se
