Ramesh Manchala

I am an accomplished IT professional with 8 years of industry experience, including 5 years specializing in DevOps. I have a strong skill set in cloud technologies like AWS, Jenkins, Git, Terraform, Docker, and Kubernetes. Throughout my career, I have successfully implemented DevOps best practices, automated processes, and resolved complex technical issues. I am currently seeking a challenging role where I can leverage my extensive experience in IT and DevOps to contribute to the success of innovative projects.

At EPAM, I work as a Senior System Engineer - DevOps, where I Designed and automated cloud exposure scenarios across AWS, using Terraform, creating repeatable lab environments that mirror real-world attack paths through services like EC2, load balancers, CloudFront, etc. so Wiz can validate its exposure graph and detections. Built minimal, targeted Infrastructure as Code topologies that intentionally chain public entry points, network constructs, and internal services, helping Wiz test how well the platform discovers relationships, propagates reachability, and surfaces risky internet-exposed assets. Designed and implemented an S3 disaster recovery strategy by building Terraform modules that provision primary and DR buckets across regions, configure one‑way and bidirectional cross‑region replication (CRR), enforce encryption and lifecycle policies, and automate IAM for secure replication and access control. Engineered an active‑passive S3 Multi‑Region Access Point (MRAP) architecture that uses a Lambda‑driven routing controller invoked from Terraform to submit MRAP route updates, ensuring the primary bucket receives 100% traffic in steady state while the DR bucket remains passive.

Prior to EPAM, I worked at CoinDcx as a Senior Software Engineer. In this role, I Implemented CI/CD pipelines using Jenkins, Git, Docker and Argo CD to automate software delivery processes, resulting in a 30% reduction in deployment time. Managed infrastructure as code using Terraform to provision and maintain AWS resources, ensuring scalability and reliability. Utilized Kubernetes for container orchestration, improving application deployment efficiency and resource utilization by 40%. Implemented monitoring solutions using Grafana and Prometheus, enabling real-time visibility into system performance and proactive issue resolution. Developed custom scripts in Python for AWS Lambda functions in terms of Cloud Cost Optimization.