Sai Pruthvi Singama

Developed and deployed a scalable, cloud-native customer support chatbot using AWS Lambda, API Gateway, and S3, reducing inquiry resolution time by 30%. Designed and implemented a Retrieval-Augmented Generation (RAG) pipeline with AWS Textract and PySpark to process over 15 million documents, increasing answer accuracy by 23%. Built a real-time sentiment analysis module using Python and Hugging Face Transformers for proactive customer issue escalation. Collaborated with ML and Data Engineering teams in Agile Scrum, increasing sprint velocity by 20%. Engineered serverless data pipelines with AWS DynamoDB and S3 for conversational data, enhancing analytics readiness. Integrated third-party CRM APIs enriching chatbot accuracy by 25%. Automated CI/CD pipelines with AWS CodePipeline, CodeBuild, and Spinnaker, reducing production issues by 35% and ensuring zero downtime for 15M+ daily users.

Developed and deployed a scalable, cloud-native customer support chatbot using AWS Lambda, API Gateway, and S3, reducing inquiry resolution time by 30%. Designed and implemented a Retrieval-Augmented Generation (RAG) pipeline with AWS Textract and PySpark for document ingestion and vectorization, improving answer accuracy by 23% and reducing irrelevant responses by 40%. Built a real-time sentiment analysis module using Python and Hugging Face Transformers to classify customer queries by emotional tone, enabling proactive escalation. Collaborated with Machine Learning and Data Engineering teams in an Agile Scrum environment, increasing sprint velocity by 20%. Engineered serverless data pipelines with AWS DynamoDB and S3, improving data integrity and analytics readiness. Integrated third-party CRM APIs and knowledge bases to enhance chatbot functionality, increasing informational accuracy by 25%. Automated CI/CD pipelines using AWS CodePipeline, CodeBuild, and Spinnaker with canary deplo

Developed scalable web applications with Spring MVC, integrating RESTful and GraphQL APIs, and secure OAuth2 authentication. Built high-performance microservices with Spring Boot and gRPC, reducing payment processing latency by 40% and supporting over 5,000 TPS. Optimized PostgreSQL databases for real-time UPI transaction processing, cutting latency by 35% and improving throughput to 1,000+ TPS. Led testing with JUnit, Mockito, and Postman achieving 95% code coverage and reducing defects by 45%. Migrated legacy monoliths to AWS EKS with Istio and auto-scaling, achieving 99.99% availability and reducing cloud costs by 25%. Designed React.js frontends with Redux improving UI development speed by 30% and Core Web Vitals by 15%. Mentored 3 junior engineers facilitating onboarding and production capability within 3 months.