DevOps Engineer(AI)

Capgemini; Brussel Hoofdstad; On-site; EUR 70,000 - 110,000; Full time

Job summary

Capgemini Belgium is seeking a highly skilled DevOps Engineer with AI/ML platform experience to design, implement, and maintain scalable cloud infrastructure supporting AI-driven applications.

The role focuses on CI/CD automation, cloud orchestration, and MLOps practices to enable reliable deployment, monitoring, and cost optimization for AI solutions across AWS, Azure, and GCP. Collaboration with Data Scientists and AI Engineers is essential.

Qualifications

• 4+ years in DevOps, Cloud Engineering or Site Reliability Engineering.
• Experience with Azure, AWS or GCP.
• Infrastructure as Code: Terraform or Ansible.
• Linux administration, scripting (Python, Bash, PowerShell) and networking basics.
• Experience deploying and managing AI/ML workloads and MLOps platforms.

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.

Skills

DevOps

Cloud engineering

SRE

MLOps

AI/ML deployment

Tools

Terraform

Ansible

Docker

Kubernetes

Job description

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.
• 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.