DevOps / Platform Engineer

Marvelxai — Netherlands · Posted ~22 hours ago

Full-time Hybrid

Skills

Kubernetes AWS Google Cloud Platform Microsoft Azure Terraform GitLab CI/CD Docker Observability Infrastructure as code Cloud infrastructure Production operations Security Reliability engineering GCP Azure

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Summary ✨ AI‑Generated

Own and evolve a production-grade cloud platform supporting sophisticated AI workloads. You will operate Kubernetes across multiple major cloud providers, build infrastructure with Terraform, maintain CI/CD pipelines, containerize services, implement comprehensive observability, and continuously improve reliability, security, and cost efficiency.

Highlights

Full-time hybrid platform role with broad ownership of production Kubernetes and multi-cloud infrastructure. The position combines infrastructure automation, CI/CD, observability, security, reliability, and support for AI/ML workloads.

Description

About MarvelX 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. 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 workloadsBuild and maintain infrastructure across AWS, GCP, and AzureDefine infrastructure as code using TerraformBuild and maintain GitLab CI/CD pipelinesContainerize and deploy services using DockerImplement observability: metrics, logs, tracing, alertingSupport AI/ML workloads (model serving, batch jobs, GPU workloads)Improve reliability, security posture, and cost efficiencyPartner with engineering to design production-ready architectures What we’re looking for Strong hands-on experience operating Kubernetes in productionExperience with at least one major cloud provider (AWS, GCP, or Azure); multi-cloud experience is a plusSolid Terraform experience managing real infrastructureGitLab CI/CD or similar pipeline tooling experienceStrong Docker fundamentalsExperience 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 experienceHelm or KustomizeExposure to security and compliance environments (SOC 2, ISO 27001) Why join Own the platform of a production AI companySmall, senior, highly technical teamDirect impact on reliability, security, and scaleCompetitive salary + equity