DevOps Engineer(AI)

Capgemini; Brussel Hoofdstad; On-site; EUR 90,000 - 130,000; Full time

Job summary

Capgemini is seeking a DevOps Engineer with AI experience to design, implement, and maintain scalable cloud infrastructure for AI-driven applications. The role focuses on CI/CD, IaC, and container orchestration across major cloud providers.

You will work with Data Scientists and Software teams to deploy, monitor, and optimize AI solutions, ensuring reliable, secure, and cost-effective operations.

Qualifications

• 4+ years of experience in DevOps, Cloud Engineering, or SRE.
• Strong experience with Azure, AWS, or GCP.
• Hands-on experience with containerization and CI/CD tools; experience with AI/ML workloads a plus.

Responsibilities

• Design, implement, and maintain CI/CD pipelines for cloud-native and AI applications.
• Manage and optimize infrastructure on AWS, Azure, or GCP.
• Automate deployment, monitoring, and scaling using IaC tools (Terraform, Ansible, etc.).
• Support AI/ML model deployment, versioning, and lifecycle management using MLOps practices.
• Implement containerization and orchestration using Docker and Kubernetes.
• Monitor system performance, reliability, security, and cost optimization.
• Collaborate with Data Scientists, AI Engineers, and Software teams to operationalize AI solutions.

Skills

DevOps experience

MLOps experience

Python scripting

Linux administration

Networking fundamentals

Cross-functional collaboration

Tools

Docker

Kubernetes

Jenkins

GitLab CI/CD

GitHub Actions

Azure DevOps

Terraform

Ansible

Job description

DevOps Engineer with AI Experience

Location: Brussels, Belgium

Employment Type: Permanent / Full-Time

Job Summary

We are seeking a highly skilled DevOps Engineer with AI/ML platform experience to design, implement, and maintain scalable cloud infrastructure supporting AI-driven applications. The ideal candidate will have expertise in DevOps automation, CI/CD, cloud technologies, containerization, and MLOps practices to enable efficient deployment and monitoring of AI solutions.

Key Responsibilities:

• Design, implement, and maintain CI/CD pipelines for cloud-native and AI applications.
• Manage and optimize infrastructure on AWS, Azure, or Google Cloud Platform.
• Automate deployment, monitoring, and scaling using Infrastructure as Code (Terraform, Ansible, CloudFormation).
• Support AI/ML model deployment, versioning, and lifecycle management using MLOps practices.
• Implement containerization and orchestration using Docker and Kubernetes.
• Monitor system performance, reliability, security, and cost optimization.
• Collaborate with Data Scientists, AI Engineers, and Software Development teams to operationalize AI solutions.

Required Skills:

• 4+ years of experience in DevOps, Cloud Engineering, or Site Reliability Engineering.
• Strong experience with Azure, AWS, or GCP.
• Hands-on expertise in Docker, Kubernetes, Jenkins, GitLab CI/CD, GitHub Actions, or Azure DevOps.
• Experience with Infrastructure as Code tools such as Terraform or Ansible.
• Knowledge of Linux administration, scripting (Python, Bash, PowerShell), and networking fundamentals.
• Experience deploying and managing AI/ML workloads and MLOps platforms.

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