Bangalore, India
Lead Backend Engineer · Cloud system design
Five years building scalable cloud-native systems: secure microservices, GraphQL and FastAPI services on GCP and AWS, and the CI/CD that ships them — most recently cutting deployment time by 30%. Before that, two years at IIT Gandhinagar on deep learning for brain imaging, published at Brain Informatics 2021.
Selected work
A platform that collects global trends from TikTok, YouTube and Instagram, then uses Gemini to turn the raw signal into structured insight for beauty, cosmetics and travel clients. I built the backend in Python and Node.js and the GraphQL and FastAPI microservices behind it, on Google Cloud Run.
A fee-payment REST API spanning multiple gateways, handling over 100K payments a month with reporting for administrators. I led the database and API work — Django REST Framework, Google Cloud Storage, microservices — across 15+ custom modules deployed on AWS and GCP.
My M.Tech thesis, published at Brain Informatics 2021. A 2D CNN that classifies Alzheimer’s disease from MR images, outperforming the state of the art on accuracy, sensitivity and specificity across all three brain planes.
A deep learning tool that returns the probability a chest X-ray shows COVID-19 infection, released publicly and tested by the Indian Institute of Public Health. I led it as principal investigator at IIT Gandhinagar; it was covered across national media.
In the press
Built at IIT Gandhinagar under Prof. Krishna Prasad Miyapuram, and picked up widely in June 2020.
I’m easiest to reach by email, and I read everything that lands there. My résumé has the full detail; GitHub has the code.