Karthik Mukkera

Led scalable, secure applications using React, Angular, TypeScript, and Spring Boot, increasing portal engagement by 60%. Architected HIPAA-compliant RESTful APIs and microservices with Java, .NET Core, Spring Security, and Kubernetes, improving backend scalability by 40% for real-time data processing. Managed cloud deployments on Azure and AWS, boosting system performance by 45% while optimizing uptime. Reduced defects by 40% through comprehensive testing using Selenium, Appium, and Cucumber. Automated CI/CD pipelines with Jenkins and Azure DevOps, containerizing applications with Docker and Kubernetes to achieve 99.99% uptime. Conducted SQL and Python data analysis to support clinical decisions and regulatory reporting, and designed efficient PostgreSQL and MongoDB schemas improving query performance by 30%. Collaborated with Agile teams to align features with healthcare regulations and business goals.

Led scalable and secure applications development using React, Angular, TypeScript, and Spring Boot, increasing clinician and patient portal engagement by 60%. Architected HIPAA-compliant RESTful APIs and microservices with Java, .NET Core, Spring Security, and Kubernetes, improving backend scalability by 40% for processing billions of data points in real-time. Managed cloud deployments on Azure and AWS, migrating legacy platforms to cloud-native EC2, S3, and Lambda services, enhancing system performance by 45% and optimizing uptime. Reduced production defects by 40% through comprehensive automated testing with Selenium, Appium, and Cucumber. Automated CI/CD pipelines using Jenkins and Azure DevOps, containerized applications with Docker and Kubernetes, achieving 99.99% uptime, reducing deployment failures by 20%, and shortening deployment cycles. Conducted SQL and Python data analysis to support clinical decisions while maintaining 99.9% application availability through cloud monitorin

Designed, developed, and maintained scalable client- and server-side applications using JavaScript, React, Next.js, C#, .NET Core, and TensorFlow. Reduced infrastructure costs by 40% and boosted uptime by migrating monoliths to AWS cloud-native architecture. Led migration to microservices with Kafka, reducing latency by 25% and enabling real-time insights. Accelerated deployment frequency from weekly to daily through automated CI/CD pipelines. Improved system reliability by shortening incident resolution times with root cause analysis and proactive alerting on AWS. Enhanced backend API and database query performance across SQL Server, PostgreSQL, and NoSQL, increasing system scalability by 40%.