DevOps Engineer
MarvelX AI
Amsterdam, Netherlands
2 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
EnglishJob location
Amsterdam, Netherlands
Tech stack
Artificial Intelligence
Amazon Web Services (AWS)
Azure
Bash
Linux
DevOps
Python
Prometheus
Scripting (Bash/Python/Go/Ruby)
Google Cloud Platform
Grafana
Gitlab-ci
Kubernetes
Terraform
Docker
Job description
We're looking for a DevOps / Platform Engineer to own and evolve our cloud and Kubernetes infrastructure. You will work closely with Product, Engineering, and ML to keep our platform scalable, secure, and production-ready as we grow.
This is a full-time, hybrid role (office-first, up to 1 day/week remote).
What you will do
- Own and operate Kubernetes clusters running production workloads
- Build and maintain infrastructure across AWS, GCP, and Azure
- Define infrastructure as code using Terraform
- Build and maintain GitLab CI/CD pipelines
- Containerize and deploy services using Docker
- Implement observability: metrics, logs, tracing, alerting
- Support AI/ML workloads (model serving, batch jobs, GPU workloads)
- Improve reliability, security posture, and cost efficiency
- Partner with engineering to design production-ready architectures
Requirements
Do you have experience in Terraform?, * Strong hands-on experience operating Kubernetes in production
- Experience with at least one major cloud provider (AWS, GCP, or Azure); multi-cloud experience is a plus
- Solid Terraform experience managing real infrastructure
- GitLab CI/CD or similar pipeline tooling experience
- Strong Docker fundamentals
- Experience with observability tooling (Prometheus, Grafana, ELK, OpenTelemetry, or similar)
- Linux and scripting skills (Bash, Python, etc.)
- Interest or experience supporting AI/ML systems
Nice to have
- GPU scheduling / ML platform experience
- Helm or Kustomize
- Exposure to security and compliance environments (SOC 2, ISO 27001)
About the company
MarvelX builds AI agents for regulated industries such as insurance and financial services. Our systems run in real production environments where reliability, security, and observability matter as much as model quality.