Sarthak Sinha
Engineering @Uber | xFlipkart | GenAI
Bengaluru
5+ years of work experience
Apr 20265 mosPresent
Bengaluru, Karnataka, India
Part of Segment Expansion - U4B
Feb 20224 yrs 3 mosApr 2026
Bengaluru, Karnataka, India
Worked in the Backend domain of Flipkart Marketplace, focusing on building scalable, multi-tenant, and event-driven systems across the seller and aggregator ecosystem. Designed and implemented the pipeline to onboard and authenticate China Aggregators on the Shopsy platform—forming the foundation for enabling international aggregators to operate within Flipkart’s ecosystem. Built a real-time, event-driven integration model to synchronise data and workflows with external vendor systems.
Contributed to the design of Flipkart’s APISIX-based external API gateway, collaborating closely with platform teams on routing, extensibility, and governance. Owned the design and development of the Multi-Tenancy Management Plane, delivering dynamic tenant onboarding, capability registration (rate limits, auth policies, custom flows), and tenant-isolated configuration management using strong Domain Driven Design principles.
Managed the API Sandbox pipeline to enable real-time, production-like testing for internal and external stakeholders, driving both product and technical design. Additionally worked across seller- and aggregator-facing APIs including inventory ingestion, order sync, and push notifications.
Played a key role in architecting and scaling distributed systems that are resilient, fault-tolerant, and optimized for high throughput. These systems support real-time data flows, event-driven architectures, and multi-tenant workflows critical to Flipkart’s marketplace platform.
Nov 20214 mosFeb 2022
Bengaluru, Karnataka, India
Worked as a Software Engineer in the Frontend team on a decentralized data management and tiering software product optimized for video/radar/lidar data. It runs on all resources from edge to cloud as a software blanket that provides structure and a scalable process to deliver curated, consistent, and relevant AI-ready data sets.
Jan 20217 mosJul 2021
Mumbai, Maharashtra, India
Developed a Natural language understanding model that can read user feedback of a certain ticket raised while using a service provided by the company and automatically bucket those tickets into major categories so that the debugging team can work more efficiently, and resolution of tickets can be made faster.
Further improved the model by adding time series forecasting to it to predict the chance of occurrence of any ticket in the future so that it can be resolved beforehand.
Sarthak’s AI Stack
Education
Bachelor's degree, Computer Science
Thapar Institute of Engineering & Technology
20174 yrs2021
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