• Migrated from SQS to a Kafka-based messaging system, streamlining inter-service communication and reducing message processing time by 50-60%.• Implemented AWS SQS and SNS, enhancing inter-service communication between 2+ microservices and reducing message delivery time by 50%, improving scalability by 40%.• Containerized a microservice using Docker, improving consistency, scalability, and efficiency, and streamlining deployment in CI/CD pipelines.• Created a Module Insights feature using Java Spring MVC to track regional module and client usage, improving data visibility and enabling targeted analysis for better decision-making.• Improved Flask Application performance by 40% using Python's multithreading to enhance concurrency and manage concurrent tasks, resulting in better system responsiveness.

• Implemented Redis caching with Python’s Singleton pattern, reducing response time by 60% and increasing system scalability by 20% for a Conversational Multi Chat-Bot AI simulation.• Developed an Aerospike client wrapper with the Singleton pattern in Spring Boot Application, improving reliability and scalability through efficient connection management.• Led an AI-based module test project in FLASK, simulating real-life customer interactions in a live chat environment, and resolved customer queries, demonstrating problem-solving and customer service skills.• Engineered a messaging queue system to fetch data from the queue, reducing assessment scoring processing time by 40% and improving efficiency and accuracy in data handling.• Built code stubs generation functionality for JavaScript coding questions, streamlining candidate assessments and enhancing efficiency in question scheduling