DevOps Engineer

Summary

As a Cloud DevOps Engineer at Gainwell Technologies in Chennai, TN, IN, you will be instrumental in managing CI/CD pipelines, infrastructure automation, and ensuring operational reliability for both Azure and AWS demo platforms. Your primary responsibility will be to provision, update, and decommission environments efficiently using infrastructure-as-code principles and DevOps best practices, supporting the entire demo lifecycle. This role is focused purely on product development and does not involve access to any sensitive Protected Health Information (PHI), Personally Identifiable Information (PII), or confidential client data, ensuring all work is confined to application development.

Your role in our mission

• Author, maintain, and optimize Terraform modules for Azure and AWS to enable self-service, versioned, and auditable environment lifecycles.
• Build, secure, and manage CI/CD pipelines using tools such as Azure DevOps, GitHub Actions, and Jenkins for deploying applications, configurations, and demo data.
• Integrate automated smoke and load tests into the deployment process.
• Collaborate with Infrastructure, App Config, and Product SME teams to implement feature flags, automated checks, and environment adjustments.
• Maintain comprehensive audit trails for all demo activities, including provisioning, configuration, and usage.
• Contribute to knowledge management by updating templates and modules based on post-demo feedback.
• Drive continuous improvement in environment reliability, reproducibility, and performance.

What we're looking for

• A minimum of 6 years of experience as a DevOps Engineer with in-depth knowledge of Terraform, preferably in a multi-cloud environment.
• Proficiency in scripting languages such as PowerShell, Python, and Bash.
• Demonstrated experience in implementing CI/CD pipelines within Azure and AWS environments.
• Familiarity with automated testing methodologies and environment monitoring tools.
• Experience with demo or sandbox platforms, and a background in AI/GenAI deployment is considered a significant advantage.