AI Platform Engineer: Kubernetes, Terraform & GPU Infra

CoolPeople Technology; Stockholms kommun; On-site; SEK 700,000 - 900,000; Full time

Job summary

CoolPeople Technology seeks a Platform Engineer to build and operate the AI infrastructure stack, leveraging Kubernetes, AKS, Docker, Terraform, and CI/CD tooling. You will support ML platforms, manage GPU resources, and scale clusters while integrating with enterprise environments.

Ideal candidates have 4+ years in platform roles and 1–2+ years supporting AI/ML workloads, with strong Kubernetes, Docker, and Terraform experience to drive reliable, scalable AI workloads.

Qualifications

• 4+ years in Platform Engineering, DevOps or Infrastructure Engineering.
• 1–2+ years supporting AI/ML workloads.
• Strong Kubernetes and Docker experience.
• Strong IaC experience, particularly Terraform.
• CI/CD and cloud experience.
• Hands-on experience running infrastructure for AI/ML solutions.

Responsibilities

• Build and operate infrastructure supporting AI/ML workloads.
• Manage Kubernetes environments, particularly AKS, and Docker.
• Automate infrastructure using Terraform, OpenTofu, or Pulumi.
• Build and maintain CI/CD and GitOps processes using GitLab CI, GitHub Actions, and/or ArgoCD.
• Work with MLflow, Kubeflow, or similar MLOps platforms.
• Manage GPU infrastructure, GPU provisioning, and cluster autoscaling.
• Set up and maintain vector databases and distributed storage solutions.
• Integrate modern AI platforms with enterprise environments.

Skills

Kubernetes

Docker

IaC (Terraform)

CI/CD

GitOps

MLOps platforms

GPU infrastructure

Cluster autoscaling

Vector databases

Distributed storage

Enterprise integration

Tools

AKS

OpenTofu

Pulumi

GitLab CI

GitHub Actions

ArgoCD

MLflow

Kubeflow

Job description

CoolPeople Technology seeks a Platform Engineer to build and operate the AI infrastructure stack, leveraging Kubernetes, AKS, Docker, Terraform, and CI/CD tooling. You will support ML platforms, manage GPU resources, and scale clusters while integrating with enterprise environments.

Ideal candidates have 4+ years in platform roles and 1–2+ years supporting AI/ML workloads, with strong Kubernetes, Docker, and Terraform experience to drive reliable, scalable AI workloads.