AI Platform Engineer

Schuberg Philis; Haarlemmermeer; On-site; EUR 90,000 - 120,000; Full time

Job summary

Schuberg Philis in the Netherlands is seeking an AI Platform Engineer to build and operate scalable AI workloads. You will focus on platform infrastructure, automation, and reliability to empower engineers to deploy AI workloads safely and efficiently.

The role involves working with Kubernetes platforms, deployment automation, observability, security, and developer experience, including OpenAI/Anthropic integrations and GraphRAG workloads on Neo4j in production.

Qualifications

• Experience in platform engineering, SRE or distributed systems.
• Hands-on with Kubernetes-based and cloud-native environments at scale.
• Ability to automate infrastructure and improve developer experience.

Responsibilities

• Design self-service platform capabilities using Kubernetes, Terraform and GitOps.
• Operationalize graph and vector databases and model serving workloads.
• Improve observability of AI systems in production.
• Integrate OpenAI or Anthropic-based services into the platform.
• Operationalize LangGraph workloads on Kubernetes.
• Enable GraphRAG architectures powered by Neo4j.
• Design deployment patterns to meet production standards.

Skills

Platform engineering

SRE

Infrastructure

Distributed systems

Automation

DevOps

Tools

Kubernetes

Terraform

GitOps

ArgoCD

GitHub Actions

Neo4j

GraphRAG

LangGraph

Job description

Colleague

Schiphol-Rijk

32-40 uur

Great AI doesn’t start with a great model. It starts with a great platform.

The success of an AI initiative is rarely determined by the model alone. More often, it depends on the quality of the platform underneath it.

As an AI Platform Engineer in our central Data & AI team, you’ll build the foundations that let engineers develop, deploy and operate AI workloads safely and efficiently. You’ll work on the infrastructure, automation and platform capabilities that allow teams to innovate without compromising reliability, and you’ll bridge the gap between promising technology and production reality.

Think Kubernetes platforms, deployment automation, observability, security and developer experience. Think AI workloads built around Large Language Models, retrieval systems, graph technologies and modern data platforms. Think creating an environment where engineers focus on solving problems rather than fighting infrastructure.

What you will work on

• Designing self-service platform capabilities using Kubernetes, Terraform and GitOps principles
• Operationalizing graph and vector databases, and enabling model serving workloads
• Improving the observability of AI systems running in production
• Integrating OpenAI or Anthropic-based services into our platform
• Operationalizing LangGraph workloads on Kubernetes
• Enabling GraphRAG architectures powered by Neo4j
• Designing deployment patterns so AI services meet the same standards as any other production workload

You’ll spend less time tuning models and more time making sure AI capabilities can be trusted, operated and continuously improved. This role sits at the intersection of platform engineering, software engineering and AI.

At Schuberg Philis we don’t believe in throwing solutions over the fence. The engineers building systems are responsible for running them too, and that ownership extends to AI just as much as every other technology we work with. Your impact won’t be measured by the number of clusters you manage, but by how much autonomy and confidence other engineers gain from the platform you’ve built.

We’d love to meet you if

• You care deeply about building platforms that other engineers love to use, and you’re happiest when automation replaces repetitive work
• You have a strong background in Platform Engineering, SRE, infrastructure or distributed systems
• You have extensive experience building and operating Kubernetes-based and cloud-native environments, with infrastructure automation at scale
• You’ve built and operated production environments using tools such as Terraform, ArgoCD, GitHub Actions or similar
• You understand what it takes to operationalize AI workloads in production, and technologies such as OpenAI, Anthropic, Neo4j, GraphRAG, vector databases or LangGraph are familiar territory
• You believe observability, reliability and security belong in every design conversation
• You enjoy improving developer experience through automation and self-service
• You see the gap between a successful proof of concept and a production-ready system and immediately start figuring out how to close it
• You take ownership of the result
• You get satisfaction from enabling other engineers to move faster and safer
• You are currently based in the Netherlands.