Sep 2024 – Jun 2025 · 9 mos · San Jose, California, United States · On-site

• Implemented the Free Shipping promotion project on TikTok Shop's Product Details Page (PDP), dynamically rendering voucher details and pop-ups to boost GMV, supporting QPS of 100K+ during high-traffic periods.
• Boosted user engagement and conversion rates for 100M+ users by implementing A/B experiments to analyze user behavior, delivering swift and accurate solutions with server-driven UI, achieving faster release cycles and scalable codebase.
• Contributed in redesigning the PDP module into a modular, scalable platform, enabling independent customizations of the view object reducing resource dependency, enhancing team efficiency, and modularizing the codebase for future growth.

Jun 2024 – Sep 2024 · 3 mos · Greenwich, Connecticut, United States · On-site

• Developed a new real-time system to track all live Forex trades, leveraging Vert.x asynchronous event bus to handle trading volumes of over 3M with 98% accuracy, integrating caching and persistent filtering based on user-defined criteria enhancing the usability and accuracy of system.
• Designed a feature-id-based user settings configuration, enabling field-level updates to reduce JSON payloads and avoid schema conflicts, improving scalability and reliability for risk monitoring platform.
• Spearheaded the design and implementation of a Vue.js-based library for Trade Monitors, resulting in a 60% boost in performance. This was achieved through DOM optimization, Vue reactivity, lazy loading, pagination, and component reusability, significantly enhancing the system’s scalability and responsiveness.

Jun 2023 – Aug 2023 · 2 mos · Connecticut, United States · On-site

• Revamped Risk Management tool's codebase, achieving 60% performance boost and scalability. Elevated Lighthouse score from
• 24 to 92 with DOM optimization, lazy loading, Vue reactivity, and component reuse.
• Implemented Cypress-based testing framework for Vue.js Risk Management tool, reducing manual testing by 10 hrs/week, identifying 40% more defects, and enhancing risk assessment accuracy by 30%.

Jul 2020 – Jun 2022 · 1 yr 11 mos · Mumbai, Maharashtra, India

• Redesigned a distributed, multithreaded trade posting system with Kafka, ensuring data consistency and reliability along with decoupling and asynchrony, allowing seamless processing of 90 million daily transactions.
• Transformed Net Revenue Data collation with a sliding window system, leveraging microservices and streaming data principles. Achieved an 80GB to 15GB I/O reduction and daily runtime from 8hrs to 15mins drastically improving customer insights.
• Automated revenue analysis reports for key customers, leveraging Vue.js UI, elevating customer analysis efficiency by 30%.
• Contributed to Kubernetes migration by developing Python app for generating config files and scaling applications in containers.