Implemented distributed traffic management leveraging Redis and Python, mitigating service overload, reducing request delays by 30% during unexpected peak loads.

Optimized real-time chat infrastructure by introducing rate-limiting with Redis and Elixir, enhancing readability in live streams and boosting user engagement by 20%.

Revamped notification delivery platform using RabbitMQ, Python, and asynchronous processing, improving alert delivery speed by 40% for millions of users.

Designed and deployed Whatamix feed platform utilizing DAGs and modular architecture, written in Python, enhancing content personalization and boosting discoverability by 25%.

Conducted rigorous load testing and addressed system bottlenecks with Python, Kubernetes, and performance analytics, enabling the platform to scale for 5x traffic.

Optimized database and GraphQL query performance through async I/O and resolver enhancements, reducing latency by 40% in critical workflows.

Collaborated across teams to adopt Python-based solutions for distributed systems, fostering a cooperative environment and enhancing cross-team workflows for scalability.

Optimized last-mile delivery operations by developing a FastAPI-based machine learning model with Docker and Uvicorn, reducing delivery delays and saving $4–5M annually.

Enhanced inventory reservations API scalability using actor pattern, Kubernetes, and CosmosDB, increasing throughput by 150% during peak traffic, processing 5,000 orders per second.

Rebuilt Walmart’s autocomplete backend by implementing prefix hash trees and Memcached in Kubernetes, achieving O(1) query time and reducing response latency by 20%.

Improved partner integrations by building Spark-based pipelines in GCP, enabling secure API feeds via signed URLs, reducing data processing time by 75%.

Scaled real-time data pipelines for A/B testing with Kafka, Spark, and M3DB, handling 250,000 messages/second, improving experiment metric processing to under three minutes.

Collaborated effectively with cross-functional teams to troubleshoot issues, ensure operational excellence, and maintain high-quality deliverables under tight deadlines in high-pressure environments.

Leveraged React, Redux, Material UI, and Figma to create dynamic UI features, enabling personalized product designs, increasing user satisfaction by 15%.

Drove the development of the Lifetouch mobile app using React Native, Node.js, MongoDB, and GraphQL, with exploration of potential AI-powered recommendation features.

Created AWS Resource Management Dashboards to monitor and manage AWS resources effectively by predicting future costs and redundant resources decreasing the average metric usage by 25% for DB and SQS resources.

Migrated parts of a legacy web application to a more modern React codebase, improving performance and SEO.

Implemented dynamic website navigation, improved performance, and fixed various bugs to enhance accessibility and overall user experience.

Followed an agile SDLC process with daily stand-ups, sprint planning, and retrospectives.

Conducted unit testing using tools like Jest to ensure code quality before deployment.