cloud engineer for AI workloads

Capgemini is a global business and technology transformation partner that helps organizations accelerate their digital and sustainable transition. It delivers end-to-end services and solutions across strategy, design, engineering, AI, cloud, and data in more than 50 countries.

• Build and operate highly available, scalable enterprise platforms and shared services;
• Develop reusable platform capabilities and self-service solutions that accelerate delivery across teams;
• Manage and evolve cloud and hybrid infrastructure platforms, including AI workloads, GPU-enabled environments, model serving, and data services;
• Implement resilient, cloud-native solutions optimized for performance, scalability, security, and cost efficiency;
• Implement Infrastructure as Code (IaC), CI/CD pipelines, and deployment automation aligned with Secure Development Lifecycle (SDL) practices;
• Automate operational processes, testing, and configuration management while promoting platform engineering practices that improve developer productivity and platform adoption.

• Degree in computer science, computer engineering, electronic engineering, or a similar field;
• At least 1+ years of hands-on experience with Cloud Infrastructure;
• Experience with cloud-native monitoring services;
• Experience with CI/CD pipelines and automated release management;
• Experience with Infrastructure as Code using one of the cloud hyperscalers: AWS, Azure, or GCP;
• Experience with Python and Bash for scripting and automation;
• Nice to have: Certification from any of the cloud hyperscalers: AWS, Azure, or GCP.

• Flexible work environment with working hours and office or remote work managed according to the company’s hybrid work policy;
• Access to professional communities supporting continuous learning, career development, and knowledge sharing;
• Volunteer program supporting a sustainable and inclusive future;
• Equal opportunity employer promoting equality and dignity in recruitment and employment.