DevOps Engineer

We are looking for a hands-on DevOps Engineer to join a leading and growing technology company and play a key role in building and evolving its cloud platform.

This is an opportunity to work in a highly technical, modern environment, with significant ownership and direct impact on cloud infrastructure, automation, and developer enablement.

We’re looking for an experienced DevOps professional with strong AWS and Cloud-Native expertise, hands-on Terraform experience, a strong connection to software development teams, and a passion for leveraging AI tools in day-to-day work.

Requirements:

• At least 5 years of DevOps / Cloud Engineering experience.
• Strong hands-on AWS experience. Azure experience is a plus.
• Proven experience working closely with software development teams.
• Experience deploying and operating cloud-native workloads in production.
• Experience with CI/CD platforms and automation.
• Strong Terraform / Infrastructure as Code experience.
• Comfortable working with Git and Git-based workflows.
• Hands-on experience using AI tools to improve productivity, automation, and troubleshooting.

Technical Skills:

• Strong experience with AWS cloud-native services, including Lambda, ECS, EKS, API Gateway, ALB, VPC, and serverless architectures; ability to design and operate production workloads using these services.
• Strong Terraform skills, including writing, reading, reviewing, and maintaining IaC and understanding infrastructure architecture.
• Experience building and maintaining CI/CD pipelines with GitHub Actions and working with Git-based workflows.
• Experience with multi-account AWS environments, including environment isolation and deployment strategies across Dev / Staging / Production.
• Understanding of secure networking and private connectivity, including VPC Endpoints, PrivateLink, and Private API Gateway.
• Understanding of authentication and authorization, including OIDC, Cognito, IAM, and external Identity Providers.
• Familiarity with AWS Control Tower and multi-account operating models, plus hands-on use of AI tools for automation, troubleshooting, and productivity.