Streamlined API P90 latency by 29% through the implementation of a QR code-based check-in system with Python, Django, and Redis caching, significantly enhancing participant event entry efficiency.

Accelerated server-side processing by 30% by developing custom registration forms with Python and Django, utilizing gRPC for enhanced inter-service communication.

Expedited development time by crafting a cross-platform mobile app using Flutter and a progressive web app with React and TypeScript, focusing on front-end optimization, UX, and automated CI/CD pipelines via fastlane.

Engineered a real-time notification system with Node.js, WebSocket & Google FCM and increased event interaction by 25% while integrating a payment gateway and job queue for improved transaction reliability.

Reduced search latency by 20% by architecting a scalable backend for an AI-powered medication search engine using Node.js, TypeScript, and PostgreSQL, integrating ChromaDB and Llama 3 to enhance RAG capabilities.

Boosted data extraction efficiency by 30% and cut data matching errors by developing a self-healing web scraper using fine-tuned LLMs and embedding models, ensuring accurate medication data extraction.

Trimmed API response time by 20ms by implementing an event-driven microservice architecture with AWS Lambda and Node.js, significantly improving API Requests per minute (RPM) for the prescription search engine.

Built and deployed an AI based language learning application that helped students understand Italian with near real time translations and transcriptions