Indura Vidyasekara

Designed and managed cloud infrastructure on Microsoft Azure using Terraform, built GitHub Actions CI/CD pipelines, and deployed Kubernetes workloads. Implemented Prometheus and Grafana monitoring and enforced security best practices aligned with PCI DSS, SOC 2, and ISO/IEC 27001.

Oversaw DevMLOps processes for AI-driven enterprise software, deployed ML workloads on AWS EKS using Kubeflow and KServe, and automated Kubernetes deployments with Helm and Argo CD. Contributed to 20%+ infrastructure cost optimization.

Architected enterprise-grade monitoring with Grafana, Prometheus, and AWS CloudWatch, centralized multi-cloud logs via ELK stack, and delivered AI/ML POCs with AWS SageMaker. Reduced infrastructure costs by 30% and drove 20-35% cloud spend reduction QoQ.

Led Kubernetes adoption across GKE and EKS, deployed AWS SageMaker for ML engineers, and built FAISS-based KYC data retrieval systems. Spearheaded Python backend development and integrated event-driven architectures using GCP Pub/Sub, AWS SNS/SQS, and Azure Service Bus.

Designed and configured a fully automated CI/CD lifecycle for a high-profile single-page application, achieving a 3x reduction in deployment time. Built AWS infrastructure using Terraform and implemented automated cost monitoring, achieving 17% savings on AWS operational costs.

Completed 200+ DevOps and Python projects including Django/Flask web apps, ML pipelines, and cloud infrastructure deployments. Designed AWS CloudFormation templates and developed custom CI/CD pipelines and automation frameworks.

Led DevOps infrastructure, automation tooling, and configuration management for an Agile-based healthcare platform. Built and maintained Go-based microservices using gRPC, RabbitMQ, and Kafka deployed on AWS and Azure.

Pursued a Bachelor of Science in Computer Science, focusing on core computer science principles and practices.