Innovative Software Engineer specializing in cloud-native applications, AI/ML solutions, and full-stack development. Passionate about creating scalable, efficient systems that drive business value and technological advancement.
I'm a passionate Software Engineer specializing in cloud-native applications, AI/ML solutions, and scalable system architecture. Currently pursuing my Master's in Computer Science at California State University, San Bernardino, I combine academic rigor with hands-on experience in building enterprise-grade applications.
My expertise encompasses full-stack development with modern frameworks, cloud infrastructure on Azure and AWS, machine learning implementations, and DevOps automation. I excel at transforming complex business requirements into elegant, performant solutions that drive measurable impact.
San Bernardino, CA
MS Computer Science
Tech Mahindra
Developed and maintained enterprise-level applications using modern technologies. Collaborated with cross-functional teams to deliver high-quality software solutions.
California State University, San Bernardino
Focusing on advanced software engineering, cloud computing, and system design. Maintaining excellent academic performance with a CGPA of 3.7 while working on cutting-edge projects.
Sathyabama Institute of Science and Technology
Graduated with honors. Built a strong foundation in computer science fundamentals, algorithms, and software development practices.
Cloud services and Azure platform knowledge
HackerRank certified Java developer
System automation and scripting
Security and threat assessment
Full-stack educational game leveraging Azure Functions for serverless backend, SQL Server for data persistence, and C++ for high-performance game logic. Implements real-time progress tracking, adaptive learning algorithms, and responsive UI design.
Advanced RAG system integrating Hugging Face Transformers with Elasticsearch for semantic search and FAISS for vector similarity. Implements context-aware response generation with 40% improved accuracy over baseline models.
Enterprise-grade fraud detection system utilizing AWS Textract for OCR, Rekognition for image analysis, and custom ML models. Achieves 95% accuracy in detecting document tampering with real-time processing capabilities.