Rupesh Mangal

• Multi-Tenant Migration: Migrated the backend from a single-tenant to a multi-tenant architecture, reducing the average release cycle from 3 months to 2 weeks. This resulted in a 40% reduction in cloud costs and decreased client onboarding time from 4 weeks to 3 days.
• AI Assistant: Developed an AI Assistant using NLP, Open AI to revolutionaries Point of care by suggesting diagnosis, automating documentation and referral creation, saving at least 30% of Doctors’ time.
• Framework Migration: Led the migration of the entire backend (100+ APIs) from Django to FastAPI resulting in a 100% increase in RPS and reduced response time by 30%
• Custom OCR: Developed custom OCR models using Tesseract and OpenCV to reduce reliance on Google Vision, resulting in an 80% reduction in cloud costs
• InVision: Developed a microservice using Node.js and Google Vision to detect patients from EMRs, reducing the load on the primary backend and resulting in a 40% increase in (RPS).
• Configurable Architecture: Led the migration of the application from a static to a configuration-driven architecture, enabling custom feature development and reducing delivery times by 80%.
• Notifications-service: Developed a real-time UI communication layer in the existing app for push and in-app notifications using WebSockets, supporting multiple authentication methods
• TeleHealth: Developed the backend of a TeleHealth solution using the Twilio SDK. Adopted a serverless microservices architecture to enable component-wise on-demand scalability, resulting in up to 75% cloud cost optimization.

Tech Used: OpenAI, Python, Django, MongoDB, ElasticSearch, NodeJS, ExpressJS, Docker, Redis, Celery, AWS-Lambda, Django-channels, Twilio, Locust