Senior AI Platform Engineer

Empiric; Amstelveen; On-site; EUR 90,000 - 130,000; Full time

Job summary

Empiric is seeking an experienced Platform Engineer to help build a Sovereign AI infrastructure on dedicated hardware, enabling secure, scalable AI workloads with self-managed Kubernetes.

You will contribute to an internal Developer Platform (Backstage) and automate deployments with ArgoCD, Terraform/OpenTofu, while ensuring strong security, data sovereignty, and compliance across enterprise environments.

Qualifications

• Strong production experience with self-managed Kubernetes
• Expertise in GitOps tooling (ArgoCD/Flux) and IaC
• Software engineering experience in TypeScript, Go or Python
• Experience designing APIs, automation and self-service platform capabilities
• Solid understanding of Kubernetes security, OIDC, network policies and software supply-chain security

Responsibilities

• Designing and operating self-managed Kubernetes platforms supporting AI workloads
• Building an Internal Developer Platform using Backstage for self-service onboarding and deployment
• Engineering automated deployment workflows using ArgoCD, GitOps and OpenTofu/Terraform
• Migrating AI workloads from public cloud to sovereign infrastructure with NVIDIA GPUs and Ceph storage
• Developing platform services and APIs using TS/Go/Python
• Implementing secure identity and secrets management with Keycloak/OpenBao
• Supporting GPU resource allocation and platform scalability

Skills

Self-managed Kubernetes

GitOps

API design

Programming: TS/Go/Python

Security & IAM

Tools

ArgoCD

Flux

Terraform

OpenTofu

Backstage

Ceph

NVIDIA GPU Operator

Job description

Are you an experienced Platform Engineer interested in building next-generation Sovereign AI infrastructure?

We're supporting a major European technology organisation developing a Sovereign AI Platform designed to deliver secure, scalable AI capabilities without reliance on public cloud hyperscalers.

This is an opportunity to engineer the underlying infrastructure powering enterprise AI workloads, including GPU-accelerated inference, self-service model deployment and highly secure, air-gapped Kubernetes environments.

You'll work within a specialist engineering team building a production-grade AI platform on dedicated infrastructure, supporting organisations with strict data sovereignty, security and compliance requirements.

What You'll Be Doing:

• Designing and operating self-managed Kubernetes platforms supporting mission-critical AI workloads.
• Building an Internal Developer Platform using Backstage, enabling self-service onboarding and AI model deployment.
• Engineering automated deployment workflows using ArgoCD, GitOps and OpenTofu/Terraform.
• Supporting the migration of AI workloads from public cloud to sovereign infrastructure using NVIDIA H200 GPUs, Ceph storage and high-performance networking.
• Developing platform services and APIs using TypeScript, Go or Python.
• Implementing secure identity, access management and secrets management using technologies such as Keycloak and OpenBao.
• Supporting GPU resource allocation, model-serving infrastructure and platform scalability.

What We're Looking For:

• Strong production experience with self-managed Kubernetes, ideally on bare-metal or private cloud infrastructure.
• Expertise in GitOps, ArgoCD/Flux and Infrastructure as Code.
• Software engineering experience with TypeScript, Go or Python.
• Experience designing APIs, automation and self-service platform capabilities.
• Strong understanding of Kubernetes security, OIDC, network policies and software supply-chain security.
• Experience working across complex enterprise infrastructure environments.
• Comfortable collaborating with technical teams and presenting solutions to stakeholders.

Nice to Have:

• Backstage / Internal Developer Platforms.
• NVIDIA GPU Operator and GPU-accelerated Kubernetes environments.
• Envoy Gateway, Keycloak or SpiceDB.
• Experience with air-gapped infrastructure or regulated environments.
• Exposure to AI inference platforms, LLM deployment or model-serving infrastructure.

Why Consider This Opportunity?

You’ll have the opportunity to work on a technically challenging Sovereign AI programme, combining Kubernetes, GPU infrastructure, platform engineering and enterprise AI.

This is a hands-on engineering position with significant technical ownership and the opportunity to help shape a growing AI platform from its early stages.