Rigoberto – Node.js, React, Next.js

Real-time AI-powered drive-thru ordering platform used in physical restaurant locations. The application allows customers to place orders through an in-house AI system while the frontend interface updates the order instantly on customer-facing screens. The platform was designed as a multi-brand solution, allowing different restaurant brands to customize the UI, layout, and visual components while using the same core system.

• Built a real-time React application used in physical drive-thru screens for live customer ordering.
• Implemented WebSocket-based synchronization to update the order state instantly while the AI processed the conversation.
• Designed a multi-brand architecture where the same platform could dynamically adapt UI, themes, and layouts for different brands.
• Improved initial page responsiveness by 60% by implementing a Server-Side Rendering (SSR) strategy using Next.js.
• Reduced image sizes by up to 90% by designing a performance-optimized image delivery pipeline.
• Reduced unnecessary React re-renders across critical flows to improve responsiveness under heavy usage.
• Optimized backend performance and database queries to improve API response times and system stability.

Backend platform used to power multiple production services, focused on performance, scalability, and reusable infrastructure. The platform handled authentication, authorization, database access, and high-performance API communication across several applications.

• Reduced database read response time by 40% by migrating MySQL from AWS Serverless V1 to Serverless V2.
• Reduced API response time by 35% by optimizing the codebase and improving the DynamoDB integration.
• Designed and implemented a reusable RBAC middleware package used across multiple Node.js services.
• Refactored large parts of the codebase to reduce complexity by 20%.
• Improved scalability and maintainability of production APIs.
• Worked mainly on backend architecture, performance optimization, and database improvements.

Customer-facing e-commerce platform designed to provide a fast and reliable checkout experience. The platform supports multiple payment methods, product purchases, and real-time user interactions across desktop and mobile devices.

• Redesigned and optimized the checkout flow to improve usability and performance.
• Reduced shopping cart abandonment rate by 15%.
• Increased available payment methods by 200% by integrating additional payment providers using SFCC connectors.
• Improved platform security by auditing and updating outdated dependencies and libraries.
• Contributed to performance improvements in critical user-facing flows.
• Worked across both frontend and backend features in a production environment.

Internal single-page application used by a government organization in the healthcare sector to manage and track invoices submitted by hospitals and healthcare providers. The platform allowed users to review invoices, validate information, and generate reports used for internal financial processes.

• Refactored parts of the existing SPA to improve maintainability and code structure.
• Reduced code complexity by 25% through architecture and logic improvements.
• Improved API response time by 35% by creating optimized queries with proper indexing.
• Implemented a reusable validation library that reduced new bugs by 30%.
• Worked across both frontend (SPA) and backend (Node.js + MongoDB) features.
• Improved overall stability and reliability of the application in production.