DevOps Engineer(AI)

Capgemini; Brussel; Sur place; EUR 70 000 - 95 000; Plein temps

Résumé du poste

Capgemini Brussels is seeking a DevOps Engineer with AI/ML platform experience to design, implement, and maintain scalable cloud infrastructure for AI-driven apps. You will automate CI/CD pipelines, manage cloud infrastructure, and apply IaC practices to enable reliable deployment and monitoring of AI solutions.

You will collaborate with Data Scientists, AI Engineers, and Software teams to operationalize AI.

Qualifications

• 4+ years of experience in DevOps, Cloud Engineering, or Site Reliability Engineering.
• Hands-on experience with cloud platforms (Azure, AWS, or GCP).
• Proficiency with CI/CD tools and pipelines.
• Experience with IaC tools such as Terraform or Ansible.
• Strong Linux, scripting (Python, Bash, PowerShell), and networking fundamentals.
• Experience deploying AI/ML workloads and MLOps platforms.

Responsabilités

• Design, implement, and maintain CI/CD pipelines for cloud-native and AI applications.
• Manage and optimize infrastructure on cloud providers (AWS, Azure, GCP).
• Automate deployment, monitoring, and scaling using IaC tools.
• Support AI/ML model deployment and lifecycle management.
• Implement containerization and orchestration with Docker and Kubernetes.
• Monitor performance, reliability, security, and cost.

Connaissances

DevOps

Cloud engineering

SRE

CI/CD

MLOps

AI/ML workloads

Outils

Docker

Kubernetes

Terraform

Ansible

Jenkins

GitLab CI/CD

GitHub Actions

Azure DevOps

Description du poste

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.