CV

Summary

Backend focused Full Stack Engineer with 5 years of zero-to-one engineering ownership, designing and scaling mission-critical services. Adept in responsive designs, caching architectures and cross-functional delivery across product and engineering.

Education

Master of Information Systems Management - Specialization in Software Engineering, Carnegie Mellon University, Pittsburgh, PA (August 2025)
- GPA: 4.0/4.0
- Coursework: Machine Learning, Deep Learning, AI Engineering and MLOps, Distributed Systems, Object Oriented Programming in Java, Database Management Systems, Linear Programming, Agile Methods, Data Structures and Algorithms
Bachelor of Technology in Electrical Engineering, Delhi Technological University (Formerly Delhi College of Engineering), New Delhi, India (June 2019)
- GPA: 3.78/4.0 (First Class with Distinction)

Professional Experience

Cure.fit - Fitness Tech Unicorn, Bangalore, India

Full Stack Software Engineer - E-Commerce (June 2019 - July 2024)

Designed and led the integration of Cult.sport into an internal telesales platform, including product modeling, discount logic, customer lifecycle management, and telesales agent UI, driving a 10% revenue increase.
Cross-functioned with central payments team to implement a multi-tenant delayed/failed payments and fulfillment processor, addressing payment gateway webhook delays/failures. Increased conversion rates by 3.9% and net revenue by 0.8%.
Optimized system performance by building a caching service, onboarding in-memory caches for multiple micro-services. Led to 30% drop in database load, lower infrastructure costs and ~20% faster server startup times through AWS Lambda triggers.
Built a web scraping scheduler engine to extract 10,000+ SKUs daily from marketplaces using webscraper.io and SmartProxy, saving ~3 days/week of manual effort by 3 analysts and accelerating pricing decisions and catalog quality.
Redesigned address management flows for Cult.sport, adding features like address editing, auto-completion, location detection, and order confirmation, reducing order cancellations by 8% and increasing addresses added per user by 1.6.
Drove a strategic initiative to deploy low-code tools Appsmith and Retool on EC2 instances within a secure VPC with VPN-only access, integrating with internal services to power 100+ critical dashboards and cutting development time by ~80%.
Integrated MoEngage on Cult.sport for personalized event-driven CRM interactions, supporting ~1M daily user communications and 1M website events. Enabled two-way interaction with internal services using SQS, handling ~100k daily events.
Migrated critical endpoints from Node.js Backend-for-Frontend (BFF) to Spring Boot reducing latency from 350ms to ~100ms.
Led frontend development of Food Marketplace app from scratch using React Native and Redux; built Node.js/TypeScript backend supporting orders, taxes, discounts, and user feedback, onboarding 200+ vendors and 50k+ users within 6 months.
Developed responsive mobile screens in React Native and integrated with a Node.js Backend-for-Frontend (BFF) using Inversify.js and TypeScript, ensuring user data privacy and security through minimal and controlled data exposure.

Technical Skills

Languages: Java, Python, SQL, JavaScript, Typescript, HTML, CSS, Bash (Shell), C++
Frameworks/Libraries: Spring Boot, React, React Native, Redux, Node.js, Express.js, Gulp, PM2, JUnit, Nose2, Jest
Databases/Tools: MySQL, PostgreSQL, MongoDB, Redis, Maven, NPM, GCP, AWS, Docker, Kubernetes, Kafka, Coralogix, Splunk, JWT, OAuth, Datadog, JIRA, Postman, git
Others: Software Development Life Cycle (SDLC), Agile Principles, Stakeholder Management, Test Driven Development (TDD)

Academic Projects

AI Sentiment Analysis Platform - CMU & Harley-Davidson Collaboration

Developed a Django app using Hugging Face, PyTorch, NumPy and pandas for automated sentiment analysis of comments.
Containerized the application with Docker and delivered a production-ready image for Harley-Davidson’s internal deployment.

Movie Recommender System

Deployed Django application on a VM with load balancer using Docker containerization and SQLite DB serving 1M users.
Automated CI/CD pipelines with Jenkins for deployment and implemented Kubernetes-based blue-green deployments; configured GitHub Actions for pull request test automation using Nose2.
Integrated collaborative filtering model with telemetry (Prometheus, Grafana) to monitor model drift, automate retraining, and dynamically update model weights from Docker-mounted volumes.

Goal Keeper (GoalLive)

Implemented a Streamlit-based Python application to identify user’s free time slots using Google Calendar API.
Recommended football matches, nearby restaurants (via geolocation and Yelp API), and online match streaming options.
Scraped match schedules using Selenium headless browser (Chrome) driver and improved performance through caching.

Publications

A novel hybrid architecture for classification of power quality disturbances

Arshiya Aggarwal, Nisheet Das, Mansi Arora, Dr. M.M. Tripathi

Attention-guided deep convolutional neural networks for skin cancer classification

Arshiya Aggarwal, Nisheet Das, Indu Sreedevi