Portfolio
My Projects
A collection of projects showcasing my expertise in full-stack development, AI integration, and backend engineering. Each project represents real-world problems solved with modern technologies.
AI Content Platform
A sophisticated platform for generating, managing, and publishing AI-assisted content at scale.
Problem
Creating quality content at scale is time-consuming and resource-intensive for most organizations.
Solution
Built a RAG-powered system that ingests brand guidelines and generates contextually relevant content. Integrated with popular publishing platforms for seamless workflow.
Outcome
Reduced content creation time by 70% while maintaining quality. Powered by Claude AI and vector databases for semantic search.
Real-time Analytics Dashboard
Enterprise-grade dashboard for monitoring and analyzing system metrics across distributed infrastructure.
Problem
Teams lacked real-time visibility into system performance metrics and needed complex custom dashboards.
Solution
Created a modular dashboard system with WebSocket support for live data updates. Built custom visualization components for different data types.
Outcome
Enabled teams to respond to issues 5x faster. Processed 1M+ events per second with <100ms latency.
LLM Fine-tuning Pipeline
Automated pipeline for fine-tuning large language models on domain-specific data.
Problem
Generic LLMs perform poorly on specialized domains without extensive prompt engineering.
Solution
Created an end-to-end pipeline using LoRA for efficient fine-tuning, with automatic data preprocessing and quality validation.
Outcome
Achieved 40% improvement in domain-specific accuracy. Reduced fine-tuning costs by 60% compared to traditional approaches.
Distributed Task Queue
High-performance task queue system for managing async jobs across multiple workers.
Problem
Existing solutions couldn't handle variable load with strict latency requirements.
Solution
Built a custom task queue using Redis and Python with intelligent load balancing and priority queues.
Outcome
Processed 100k+ tasks daily with <5ms p99 latency. Reduced infrastructure costs by 40%.
E-commerce Platform Rebuild
Complete redesign and rebuild of legacy e-commerce platform for 10x growth.
Problem
Monolithic architecture couldn't scale. Checkout failures during peak traffic caused significant revenue loss.
Solution
Migrated to microservices architecture using Next.js frontend and Node.js/Python backends with proper caching strategies.
Outcome
99.99% uptime, 10x faster checkout process. Handled 500k concurrent users during peak sales.
ML-Powered Recommendation Engine
Personalized recommendation system using collaborative filtering and neural networks.
Problem
Generic recommendations had low CTR. Users needed truly personalized experiences.
Solution
Implemented hybrid approach combining collaborative filtering with deep learning for cold-start problems.
Outcome
Increased CTR by 35%. Reduced computation time from hours to milliseconds using model optimization.