Vijay Kumar

• Lead deployment automation for 15+ financial microservices using GitOps (ArgoCD, Flux) and Jenkins, increasing deployment efficiency by 40% and reducing release failures by 31%. • Manage AWS infrastructure (EC2, S3, CloudWatch) for 10TB+ daily transaction data, ensuring high availability, fault tolerance, disaster recovery (AWS Backup, RDS Multi-AZ), and optimized costs. • Containerize applications using Docker and Kubernetes, improving system scalability by 18% and supporting 30K+ real-time transactions per hour. • Migrated fragmented CI/CD pipelines from Jenkins, Bamboo, and OpenShift to GitHub Actions and CloudBees Jenkins, centralizing workflows, reducing downtime by 35%, and improving deployment reliability and release speed. • Automate monitoring, alerting, and dashboards with Python and Grafana, reducing delayed payment alerts by 12% and providing enhanced visibility across $350M+ daily transactions. • Implement and enforce security and compliance measures using IAM, HashiCorp Vault, Terraform, CloudFormation, and PCI-DSS standards, reducing unauthorized access by 40% and strengthening organizational cloud security posture.

• Deployed Azure Monitor and Blob Storage for 500+ cloud-based applications, improving response times by 13%. • Automated administrative workflows using Azure Functions, saving 30+ staff hours per month. • Supported CI/CD pipeline setup with Jenkins for learning management systems, reducing deployment errors by 17%.

• Automated AWS infrastructure provisioning using Terraform, CloudFormation, Ansible, and Docker, delivering 50+ deployments and reducing environment setup time by 26–40%. • Designed CI/CD pipelines with Jenkins, GitHub Actions, and AWS CodePipeline/ CodeBuild/ CodeDeploy, reducing deployment errors by 24–50%, minimizing downtime, and increasing release frequency by 25%. • Developed Python and Bash automation scripts to replace manual processes, improving operational efficiency by 23% and accelerating release cycles. • Managed project workflows using Jira and documented processes in Confluence, improving team task completion rate by 30% and reducing project delivery delays by 25%, enhancing collaboration and tracking effectiveness. • Implemented monitoring and logging using AWS CloudWatch, Prometheus, Grafana, and Splunk, resolving 50+ high-priority incidents/month and improving uptime by 17–50%. • Optimized AWS databases (RDS, DynamoDB) and EC2-based application workloads, improving query response times, cost efficiency, and overall application performance. • Strengthened cloud security with IAM policies, Security Groups, and AWS Secrets Manager, securing 1,000+ endpoints and ensuring compliance with PCI-DSS and enterprise standards.