Saikrishna Reddy Ragula

I'm

About

Software Engineer with 3+ years of experience building high-performance distributed systems and event-driven microservices. Expertise in Spring Boot, Kafka, and cloud-native architectures, processing 5M+ daily transactions with 99.99% uptime. Proven track record in fraud detection systems, scalable APIs, and full-stack development using React.js and modern DevOps practices.

Interests

Software Development

Data Structures

Application Development

Algorithms

Education

MS in Information Systems

August 2022 - May 2024

GPA: 3.72 / 4.0

Relevant Coursework

Distributed Systems
Database Management
Software Engineering
Cloud Computing
Data Analytics

B.Tech. in Computer Science and Engineering

August 2016 - May 2020

GPA: 8.04 / 10

Relevant Coursework

Data Structures & Algorithms
Operating Systems
Database Systems
Machine Learning
Computer Networks

Experience

American Express

Sept 2024 – Present

Software Engineer (Fraud Detection & Risk Systems), Phoenix, Arizona

Migrated legacy batch workflows to Spring Batch, boosting transaction pipeline performance by 45% across 5M+ daily card transactions using strategic indexing and partitioning.
Engineered a low-latency, event-driven microservices architecture with Kafka, processing 2M+ card lifecycle events/day with <50ms end-to-end latency for renewals, expirations, and deactivations.
Implemented OpenTelemetry-based distributed tracing and ELK observability dashboards, reducing MTTR for production incidents by 40% across core payment microservices.
Architected a multi-region, fault-tolerant disaster recovery system with automated failover and data replication, ensuring 99.99% uptime for services supporting $500M+ daily payment volume.

IBM India Pvt Ltd

Sept 2020 – Jul 2022

Application Developer (AT&T Digital Platform), Bengaluru, India

Engineered NotifyHub, a full-stack notification platform serving 250K+ users, enabling automated scheduling and multi-channel communications while processing 1M+ notifications/day.
Developed scalable Spring Boot REST APIs and React.js frontend implementing OAuth 2.0/JWT to securely deliver 1M+ notifications/day.
Delivered a real-time dashboard using React, Redux, and Hooks, improving rendering efficiency and reducing UI load time by 35% through component optimization and virtualized lists.
Optimized backend performance by 40% using Oracle PL/SQL tuning and a Redis caching layer for preference and keyword-based queries.
Contributed to Jenkins CI/CD pipelines with Dockerized services deployed on AWS EC2, enabling consistent zero-downtime production releases.

Projects

Intelligent Document Q&A System with RAG

Python · LangChain · OpenAI API · Pinecone · FastAPI · React.js

Developed a retrieval-augmented generation (RAG) application enabling natural language queries across 10K+ technical documents, using LangChain for orchestration, OpenAI embeddings with Pinecone vector database for semantic search, and FastAPI backend serving React.js frontend, achieving 85% answer accuracy with <2s response time.

Real-Time Stock Market Analytics Dashboard

React.js · Node.js · Python · Kafka · MongoDB

Built web application using React.js and Node.js to visualize live stock price movements and portfolio analytics for 100K+ data points/second, integrating Python-based calculations with Kafka streaming for real-time market data processing and MongoDB for historical data storage.