DevOps Engineer(AI)

Capgemini

Brussel, Belgium

3 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

4 years minimum

Working hours

Regular working hours

Job source

www.adzuna.be

Tech stack

Artificial Intelligence Amazon Web Services Microsoft Azure Bash Shell Cloud Computing Cloud Engineering Continuous Integration DevOps Github Monitoring of Systems Python (Programming Language) Machine Learning

+20 more

Networking Basics Windows PowerShell Reliability Engineering Ansible Azure Machine Learning Software Engineering Management of Software Versions Scripting Google Cloud Cloudformation Containerization Gitlab-ci Kubernetes Infrastructure Automation Frameworks Deployment Automation Machine Learning Operations Virtual Agents Terraform Docker Jenkins

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., * 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.

Requirements

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.