DevOps Engineer(AI)
Il y a 3 heures
Brussels, Brussels, Belgique
Capgemini
Temps plein
Gratuit avec email ou Google
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Gratuit avec email ou Google
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.
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.