AI-Driven DevOps Engineer: Cloud Pipelines & Scale

Whatsnext Ai; Rotterdam; Hybrid; EUR 65,000 - 100,000; Full time

Job summary

Whatsnext Ai is seeking a DevOps engineer to design, build and scale CI/CD pipelines for AI workloads in GCP/AWS. You will manage containerised environments with Docker and Kubernetes, collaborate with AI engineers, and ensure reliability through monitoring and incident response.

The role focuses on infrastructure automation, cloud cost control, security, and deployment standards across projects, with opportunity to shape DevOps practices as the team grows.

Qualifications

• 3-7 years in DevOps, cloud infrastructure or platform engineering.
• Hands-on production experience with GCP and/or AWS.
• Strong Docker, Kubernetes and infrastructure-as-code (Terraform or similar).
• Experience building and maintaining CI/CD pipelines.
• Familiarity with AI/ML workloads: model serving, GPU instances, vector databases.
• Strong problem-solving skills and a bias toward automation.
• Excellent Dutch and strong English.

Responsibilities

• Design and maintain CI/CD pipelines for AI workloads on GCP and AWS.
• Set up and manage containerised environments with Docker and Kubernetes.
• Work with AI engineers to streamline development-to-production.
• Monitor system performance, set up alerting and respond to incidents.
• Manage cloud infrastructure - cost, scaling and security.
• Define and enforce deployment standards across projects.
• As the team grows, establish DevOps standards and onboard new engineers.

Skills

CI/CD pipelines

Docker

Kubernetes

GCP

AWS

IaC (Terraform)

Automation

Dutch

English

Tools

Terraform

Job description

Whatsnext Ai is seeking a DevOps engineer to design, build and scale CI/CD pipelines for AI workloads in GCP/AWS. You will manage containerised environments with Docker and Kubernetes, collaborate with AI engineers, and ensure reliability through monitoring and incident response.

The role focuses on infrastructure automation, cloud cost control, security, and deployment standards across projects, with opportunity to shape DevOps practices as the team grows.