AI Platform Engineer

Ampstek; Stockholms kommun; On-site; SEK 1,200,000 - 2,100,000; Full time

Job summary

Ampstek in Stockholm is seeking an AI Platform Engineer to build and automate the GPU-enabled VMware Cloud Foundation and Kubernetes platform that the AI software stack runs on.

You will deploy and configure VCF on GPU hardware, set up VKS or Tanzu for GPU workloads, implement infrastructure as code for reproducible cluster lifecycles, and integrate with Active Directory/SSO with RBAC and audit logging.

Qualifications

• Hands-on deployment and configuration of VMware Cloud Foundation 9.x.
• Kubernetes on VMware (VKS or vSphere with Tanzu) in production.
• NVIDIA GPU enablement on vSphere (vGPU profiles or GPU passthrough, host drivers).
• Infrastructure as code with Terraform or Ansible, managed in Git.

Responsibilities

• Deploy and configure VMware Cloud Foundation on GPU-equipped hardware and validate cluster readiness.
• Deploy vSphere Kubernetes Service for GPU workloads.
• Implement infrastructure as code for reproducible cluster lifecycle.
• Integrate the platform with Active Directory and single sign-on.
• Set up governed self-service of Kubernetes namespaces, workloads, and resources with RBAC and audit logging.

Skills

Hands-on deployment

Kubernetes on VMware in production

NVIDIA GPU enablement on vSphere

Infrastructure as code (Terraform/Ans

Tools

VMware Cloud Foundation

vSphere with Tanzu / VKS

Terraform

Ansible

Git

NSX

Job description

Role : AI Platform Engineer (VCF and Kubernetes on GPU infrastructure)

Location : Stockholm,Sweden

Employment Type : Employment Payroll Contract

Contract : 12+ Months

Job Description:

Builds and automates the GPU-enabled VMware Cloud Foundation and Kubernetes platform that the AI software stack runs on.

Key responsibilities:

• Deploy and configure VMware Cloud Foundation (ESXi, vSAN, NSX, SDDC Manager) on GPU-equipped hardware, and validate cluster readiness, networking and GPU enablement.
• Deploy vSphere Kubernetes Service (VKS) version 1.33 or later for GPU workloads.
• Implement infrastructure as code so cluster creation and lifecycle operations are fully reproducible.
• Integrate the platform with Active Directory and single sign-on for user and service authentication.
• Set up VCF Automation for governed self-service of Kubernetes namespaces, workloads and resources, with role-based access control and audit logging.

Must-have:

• Hands-on deployment and configuration of VMware Cloud Foundation 9.x.
• Kubernetes on VMware (VKS or vSphere with Tanzu) in production.
• NVIDIA GPU enablement on vSphere (vGPU profiles or GPU passthrough, host drivers).
• Infrastructure as code with Terraform or Ansible, managed in Git.

Nice to have:

• VCF Automation or Aria Automation
• NSX networking and security
• Active Directory / SSO integration for Kubernetes
• VCP-VCF or CKA certification
• Experience escalating technical cases to Broadcom/VMware or NVIDIA

Role 1: AI Platform Engineer (VCF and Kubernetes on GPU infrastructure)

Builds and automates the GPU-enabled VMware Cloud Foundation and Kubernetes platform that the AI software stack runs on.

Key responsibilities

• Deploy and configure VMware Cloud Foundation (ESXi, vSAN, NSX, SDDC Manager) on GPU-equipped hardware, and validate cluster readiness, networking and GPU enablement.
• Deploy vSphere Kubernetes Service (VKS) version 1.33 or later for GPU workloads.
• Implement infrastructure as code so cluster creation and lifecycle operations are fully reproducible.
• Integrate the platform with Active Directory and single sign-on for user and service authentication.
• Set up VCF Automation for governed self-service of Kubernetes namespaces, workloads and resources, with role-based access control and audit logging.

Must-have:

• Hands-on deployment and configuration of VMware Cloud Foundation 9.x.
• Kubernetes on VMware (VKS or vSphere with Tanzu) in production.
• NVIDIA GPU enablement on vSphere (vGPU profiles or GPU passthrough, host drivers).
• Infrastructure as code with Terraform or Ansible, managed in Git.

Nice to have:

• VCF Automation or Aria Automation
• NSX networking and security
• Active Directory / SSO integration for Kubernetes
• VCP-VCF or CKA certification
• Experience escalating technical cases to Broadcom/VMware or NVIDIA

Not a fit:

• VMware administrators without Kubernetes experience
• Kubernetes engineers without VMware experience