Ankit Rawat is a Senior Software Engineer with over 12 years of experience across monetization platforms, sales technology, and large-scale distributed systems, building and scaling products that serve millions of users globally.
Ankit Rawat currently serves as Senior Software Engineer at Meta Platforms (October 2023 to present), where he works within the Monetization organization on high-impact billing and payments infrastructure. He is leading the effort to improve performance of the WhatsApp Business Payment flow, which encompasses a frontend revamp, a redesign of the payment and WhatsApp integration, and GraphQL optimization. He designed and implemented a cross-functional user observability platform for the Billing and Payments organization that directly impacted over 100 teams, giving data scientists and stakeholders deeper visibility into user behavior and access patterns. The insights surfaced through this work identified Instagram's new payment surface as a high-impact business opportunity. He also designed and implemented a solution that reduced network log data packet size by 20% while preserving data integrity, producing terabytes of daily storage savings. In addition, he led a cross-team initiative involving three or more teams to reduce the error rate of billing and payment systems by approximately 60% across products currently driving $20 million in business.
Prior to Meta, Ankit Rawat was a Staff Software Engineer at Wayfair within the Sales Technology organization (September 2021 to October 2023), where he led a team of eight engineers building more than three secure sales tools, including PCI-compliant IVR payment systems and encrypted multi-channel customer communication platforms spanning chat, SMS, and email. He led performance evaluation efforts across multiple senior engineering teams to increase the processing capability of the Wayfair shopping cart from 30 to 90 or more items, directly enabling a $150 million per year business line with 7% year-over-year growth for Wayfair Professionals. He led the design and development of a generative AI integration that summarized customer conversations, helping support associates understand customer history more quickly and improving the call abandon rate by 14%. He also led the development of a low-latency customer discovery tool that reduced the customer discovery phase time by 85%, including an integration with Cisco to identify specific callers for individual agents. Beyond his technical contributions, he drove operational and engineering excellence practices across more than 50 engineers and 10 or more projects spanning different teams.
Before Wayfair, Ankit Rawat was a Software Engineer at Amazon (March 2016 to May 2021). During his tenure there, he designed and implemented an idempotent adapter microservice to route requests to specific domains based on locale requirements, a service that onboarded more than 30 microservices and reduced development time by 70%. He also led the design and implementation of a code coverage dashboard covering backend systems, built with a microservices architecture incorporating batch processing, asynchronous upstreams, and AWS services including SNS, SQS, and DynamoDB, which was adopted by more than 60 teams and management groups. He additionally designed an integrated mocks solution using interceptors for unstable systems, enabling microservice certification across multiple development stages and organizations. Earlier in his career, he held Software Engineer roles at Snapdeal (Jasper Infotech) from October 2015 to March 2016, and at Yodlee Infotech from July 2013 to October 2015, where he built foundational experience in backend systems and financial technology platforms.
Ankit Rawat holds a Bachelor of Engineering in Computer Science from the University of Technology, R.G.P.V. Bhopal, earned between 2009 and 2013. His technical expertise spans distributed systems, microservices architecture, GraphQL, generative AI integration, PCI-compliant payment systems, frontend development, AWS services including SNS, SQS, and DynamoDB, and large-scale observability and data platforms.