Developed NutriAI, an enterprise-scale AI nutrition assistant designed with a microservices architecture to deliver personalized meal planning and nutrition guidance. Built the frontend using Next.js, React, TypeScript, and Tailwind CSS, while designing backend services with FastAPI, REST APIs, and WebSockets. Implemented intelligent nutrition calculations including BMI, BMR, daily calorie requirements, macronutrients, fiber, and water intake based on user demographics and activity levels. Added AI-powered meal recommendations supporting weight loss, maintenance, and muscle gain, along with health-specific guidance for diabetes, hypertension, PCOS, and high cholesterol. Integrated regional cuisine preferences, pantry-aware meal filtering, budget optimization, food allergy handling, and smart ingredient substitutions. Designed the platform for future AI enhancements with Retrieval-Augmented Generation (RAG), semantic search, vector databases, recommendation engines, OCR, barcode scanning, image-based calorie estimation, voice interactions, smartwatch integrations, clinician dashboards, and local LLM support through Ollama. Containerized the application using Docker and prepared the infrastructure for PostgreSQL, Redis, AWS deployment, monitoring, CI/CD pipelines, and scalable production deployment.