Responsible for laying down the system architecture, ensure that scalability, reliability, and availability of the system

Mentor a team of 6 engineers, code reviews, and implement the best engineering practices.

Startup new scrum teams(implement Agile methodology) while improving inter-team collaboration, resolving conflicts, and engaging with Product owners to streamline the requirements and manage technical debts.

Designed a data platform to handle data streaming from thousands of trucks. Developed various functionalities including geo-based proximity, and highly available APIs that search on over 1 billion records.

Developed and containerized multiple microservices with data-intensive features.

Worked with Prof Leila Wehbe's(https://www.cs.cmu.edu/~lwehbe/) group to develop a highly scalable and available system, that performs compute-intensive operations.

This project targets to develop a website that can generate illuminated fMRI images of the brain corresponding to given stimuli. These images are created by probing a machine learning model and helps researchers avoid the cost of actual fMRI to study the subjects.

https://boldpredictions.gallantlab.org

I am working on the Backend and scaling infrastructure development for this website.

Sinopoli's Research Lab, Cyber-Physical Systems. Computer Engineering Dept.

Developing a web backend for an algorithm to detect vulnerabilities of an IoT device.

• A legacy desktop application has been written in C++, I am writing a REST-based service to use it over the web. Technology: Flask, Python

Led a team of Engineers working on App and Web services for Analytics UI. Onboarding customers from legacy solutions - Ad Hoc Analysis to Analysis Workspace Project Converter; Activity Map - a browser plugin for analytics for links on the page(https://www.youtube.com/watch?v=_5UyOTBwlL8)

Have led the development team of 6 members for a project called RoboPM - it is an intelligent agent that automates assigning client issues to respective engineer based on her expertise in the area and history of work. Techniques: NLP, Stochastic Gradient Classification, Smart Feature selection(an Adobe's in-house patented technique)

Technology: Java, Microservices. Python, Flask, Jupyter Notebooks.