Sarthak Sinha

Software Engineer

Bengaluru, Karnataka, India4 yrs 4 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in building scalable back-end systems.
Proficient in microservices and event-driven architectures.
Strong background in natural language processing and machine learning.

Stackforce AI infers this person is a Backend-focused Software Engineer in the E-commerce industry.

Contact

Skills

Core Skills

MicroservicesSpring BootApisixApi ManagementNatural Language Processing (nlp)Machine Learning

Other Skills

API GatewayApache KafkaAzkabanBack-End Web DevelopmentBitbucketC/C++CDCCompetitive ProgrammingData StructuresDistributed SystemsDockerDomain Driven DesignDropwizardElastic Stack (ELK)Event Driven Programming

About

Graduating from Thapar Institute of Engineering & Technology with a Bachelor's in Computer Science, they are currently contributing as a Software Engineer to Flipkart's marketplace team. Their work focuses on building a Flipkart-centric gateway using APISIX to manage external traffic, implement rate-limiting policies, and onboard tenants with customizable functionality, ensuring scalable and efficient traffic flow. At Flipkart, they collaborate on enhancing seller and aggregator-facing APIs, improving inventory management, push notifications, and order synchronization. Proficient in Spring Boot, reactive programming, ELK stack, and RESTful APIs, they are motivated by creating scalable back-end systems that align with organizational goals, fostering innovation and efficiency.

Experience

Flipkart

Software Engineer

Feb 2022 – Present · 4 yrs 1 mo · 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.

APISIXDistributed SystemsMicroservicesSpring BootReactive ProgrammingEvent Driven Programming+4

Akridata

Member of technical staff-1

Nov 2021 – Feb 2022 · 3 mos · 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.

Lti - larsen & toubro infotech

Project Trainee

Jan 2021 – Jul 2021 · 6 mos · 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.