Software Engineer | Full Stack & Backend
Python · Go · React · JavaScript & TypeScript · Full Stack · Backend Systems · Databases
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PicksAIStora | Full-Stack Analytics Platform
Outperformed Pandas 3× on sort, group-by, and join operations across 100K+ row datasets by architecting an in-memory columnar query engine in Python using Apache Arrow, delivering sub-second filtering and aggregation. Shipped a production-grade Flask REST API with JWT auth and RBAC for secure multi-tenant querying, backed by PostgreSQL with per-user schema isolation. Containerized via Docker Compose with 85% test coverage and automated CI/CD via GitHub Actions. Built a React dashboard with Recharts enabling non-technical users to query and visualize large datasets without writing SQL — closing the loop from raw data to insight in under 3 clicks.
GraphQL Task Management API
Held sub-100ms p99 latency at 1,000+ concurrent WebSocket connections by designing a schema-first GraphQL API with FastAPI and Strawberry, integrating Redis DataLoader batching to eliminate N+1 query overhead. Reduced average payload size 60% on deeply nested task/subtask queries versus equivalent REST endpoints, with OAuth 2.0 PKCE flow handling auth across the full connection lifecycle.
Human-AI Collaboration for Backend Text Generation: Dynamic Content Recommendation for Websites based on Keywords
🏆 Awarded Best Paper, 3rd Place at the 2024 International Conference on Computing and Data Science. Co-developed a keyword-driven content recommendation engine leveraging GPT-based AI pipelines to dynamically generate and personalize backend website copy, reducing manual authoring time by 60%. Evaluated system output quality against human-authored baselines through user studies with 40+ participants measuring coherence, relevance, and preference scores.
Experience
tap a skill pill to exploreSoftware Engineer (Full Stack)
Aadithya Cars
Cut initial page load 75% (3.2s → 800ms) via lazy loading, code splitting, and Brotli compression, raising Lighthouse Performance score to 95+ . Scaled data ingestion 4× by replacing monolithic CSV ingestion with a chunk-based streaming pipeline, eliminating OOM crashes across 500K+ row inventory datasets. Hit 99.5% uptime by integrating third-party valuation and financing APIs with exponential-backoff retry and circuit-breaker patterns, cutting time-to-interactive by 40%. Improved SQL query performance 35% via composite index design and query plan analysis on PostgreSQL tables with 1M+ records.
Software Engineering Intern
Virtusa
Cut manual stock discrepancy errors ~40% as sole backend owner of the EMart Inventory Management System (Spring Boot, Angular, MySQL), coordinating 3 engineers and shipping real-time stock tracking, expiry alerting 2–3 days in advance, and a maker-checker approval workflow. Reduced invoice processing from ~2 days to same-day by building a SHA-256 validated CSV ingestion pipeline across 3 backend modules (Public Employment Center, Tamil Nadu EB Bill System, barcode generation), auto-generating signed PDF invoices emailed to vendors.
Research Assistant
R.M.K Engineering College
Co-authored 3 IEEE conference papers by implementing Python backend systems integrating sentiment analysis, text generation, and DenseNet medical image classification models — with one paper winning Best Paper, 3rd Place at ICCDS 2024 . Built data ingestion and preprocessing pipelines supporting 3 ML research projects under faculty supervision, contributing to experimental evaluation and manuscript preparation across 7 total citations .
Software Engineering Intern
Virtusa
Delivered a full-stack e-commerce grocery platform (Spring MVC, Angular 9+, MySQL) end-to-end in 6 weeks as team lead of 3, covering product catalog, cart, checkout, and order management across 5 core user flows. Engineered 8 REST endpoints with Hibernate ORM and Spring Security, holding sub-3s page load under simulated 50-user load during final demo review.
Software Development Intern
SAWBON
Sustained sub-250ms p95 response times at 500 concurrent users with zero downtime by building concurrent Go REST APIs using goroutines, channels, and connection pooling against MongoDB. Cut median API latency 15% and reduced DB read load 30% by implementing Redis cache-aside with TTL-based invalidation across server-rendered Remix.js components. Achieved 78% code coverage on critical service paths via unit and integration tests using Go's testing package.
Projects
Deep Neural Net IPL Predictor | Multi-Modal Win Forecasting
NewAchieved 80% test accuracy on 2025 IPL match outcomes by building a multi-modal deep learning framework integrating performance data from 13 cricket leagues across 235 players, with league-quality weighting and recency decay. Designed a Dynamic OVR rating system (55–97 scale) feeding a 4-source weighted attention transformer with learnable fusion weights, capturing phase-specific batting (Top Order, Middle, Finisher) and bowling (Powerplay, Middle, Death) performance. Boosted reliability to a Brier score of 0.24 by combining a 2-layer Graph Attention Network modeling batter-bowler matchup asymmetries with a 10,000-iteration Monte Carlo simulation engine, deployed as a Flask API with SHAP explainability at sub-2s latency.
PriceWatch | Automated Price Drop Tracker with Email Alerts
NewCut user response time to deals from hours to under 60 seconds by building a Cheerio-based scraping pipeline that parses live product prices and fires instant transactional emails via Nodemailer the moment a target price hits. Reduced redundant scrape requests ~40% across 200+ tracked products by implementing cross-user URL deduplication on hourly cron checks, lowering infrastructure cost without sacrificing freshness. Secured the platform with Supabase Auth (email/password + Google OAuth) and Row Level Security policies, plus a token-based one-click unsubscribe flow requiring no login.
Research & Publications
Automated Pneumonia Detection using DenseNet
NewCo-trained DenseNet-121 on the CheXpert chest X-ray dataset with augmentation and class-weighting to handle label imbalance, achieving 92% precision-recall AUC on the held-out test set. Benchmarked against ResNet-50 and VGG-16; DenseNet outperformed by 6% AUC via dense skip connections enabling richer feature reuse across layers.
Sentiment-Based Drug Recommendation System
Co-developed an NLP pipeline using fine-tuned BERT on domain-specific patient review corpora to classify sentiment and generate ranked drug recommendations at 88% classification accuracy . Evaluated against TF-IDF and LSTM baselines, demonstrating a 12-point F1 improvement from transfer learning with biomedical pretraining.
Stack
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Others
Contributor — PrintStruct
Open SourceContributed to PrintStruct, a Python CLI tool on PyPI that visualizes project directory structures while respecting .gitignore rules. Refactored project structure for clarity, eliminated code duplication to reduce technical debt, and improved README documentation to lower barrier for new contributors.
Best Paper Presentation — 3rd Place
Achievement · ICCDS 2024Awarded at the 2024 International Conference on Computing and Data Science for the paper 'Human-AI Collaboration for Backend Text Generation: Dynamic Content Recommendation for Websites based on Keywords'.
Microsoft Imagine Cup
HackathonBuilt a collaborative platform connecting researchers, doctors, and patients to share medical reports and treatment knowledge for rare disease research.
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Whether you're looking to build scalable infrastructure, real-time data pipelines, or just want to chat about backend systems, my inbox is always open.