Tech Stack
AWSAzureCloudDockerGoogle Cloud PlatformKubernetesTerraform
About the role
- Design and implement cloud solutions (AWS, Azure, Google Cloud) supporting AI workflows and ML services
- Ensure high availability, redundancy, and disaster recovery
- Monitor performance, conduct capacity planning, and optimize costs
- Automate infrastructure and deployment processes (Infrastructure as Code, CI/CD)
- Set up and maintain security and access controls, networking, and cloud policies
- Collaborate with the ML team to ensure models run efficiently and at scale
- Drive and contribute to cross-functional initiatives for architecture, operations, and infrastructure standards
- Take ownership in a small but growing tech team and contribute strategically to platform architecture and operations
Requirements
- A relevant degree in computer science, engineering, or similar – or equivalent professional experience
- Several years of experience as a Cloud Engineer, DevOps Engineer, or in a similar role
- Exposure to AI/ML infrastructure
- Strong experience with cloud platforms such as AWS, GCP, or Azure
- Experience with Kubernetes and Docker
- Experience with Infrastructure as Code tools (Terraform/CloudFormation)
- Solid knowledge of networking, security, and cloud operations
- Proven track record of optimizing cloud cost and performance
- Analytical mindset and problem-solving skills
- Fluent communication skills in English
- It’s a plus to have experience from a fast-paced environment, SaaS, or project-based business models