{"data":{"jobs":{"edges":[{"node":{"frontmatter":{"title":"Software Engineer II","company":"Microsoft","currentTeam":"OneDrive and SharePoint","location":"Hyderabad, India","range":"March 2023 - Present","url":"https://www.microsoft.com/","endDate":"2026-01-26"},"html":"<ul>\n<li>Built a native Android WebView module for React Native with disk-based caching and request interception, reducing load time from 12.9 seconds to 5.5 seconds</li>\n<li>Led the SharePoint News API migration, including architecture and UX changes, while mentoring 2 engineers</li>\n<li>Shipped React Native features to 3M+ users while maintaining 99.9% reliability</li>\n<li>Built a config-driven component framework that made feature development and partner onboarding 40% faster</li>\n<li>Authored the AI Harness, a contract-driven framework for spec-validated LLM-assisted engineering</li>\n<li>Led development of a brownfield app-revamp feature using the AI Harness, achieving an approximately 5x improvement in development productivity</li>\n</ul>"}},{"node":{"frontmatter":{"title":"Software Engineer","company":"Microsoft","currentTeam":null,"location":"Hyderabad, India","range":"July 2020 - March 2023","url":"https://www.microsoft.com/","endDate":"2023-03-01"},"html":"<ul>\n<li>Designed a low-latency notification system with clear API contracts and consistent UI state across partner apps in Microsoft Teams</li>\n<li>Implemented data scoping for 5+ enterprise scenarios sharing one JavaScript runtime</li>\n<li>Developed a link interception module that routed 2M+ users to the right in-app experiences with 99.9% production reliability</li>\n<li>Built in-app diagnostics that reduced debugging time by 60+ hours per month</li>\n</ul>"}},{"node":{"frontmatter":{"title":"Research Intern (Deep Learning)","company":"Samsung Research Institute","currentTeam":null,"location":"Bengaluru, India","range":"May 2019 - July 2019","url":"https://research.samsung.com/sri-b","endDate":"2019-07-01"},"html":"<ul>\n<li>Trained a TensorFlow and Keras model to replace manual calibration for wearable controllers using live sensor data</li>\n<li>Designed a specialized RNN and custom loss function that reduced error by 75%</li>\n</ul>"}},{"node":{"frontmatter":{"title":"Data Science Intern","company":"Prakshep","currentTeam":null,"location":"Bengaluru, India","range":"May 2018 - June 2018","url":"https://prakshep.com/","endDate":"2018-06-30"},"html":"<ul>\n<li>Used Sentinel-2 imagery, Python, and OpenCV to classify water bodies and agricultural land</li>\n<li>Built Z-score models over spectral indices to flag harvest windows and outlier plots for precision farming</li>\n</ul>"}},{"node":{"frontmatter":{"title":"Data Science Intern","company":"Farebond","currentTeam":null,"location":"Bengaluru, India","range":"May 2017 - August 2017","url":"https://farebond.com/","endDate":"2017-08-31"},"html":"<ul>\n<li>Built a flight-fare-lock pricing model using flight volatility</li>\n<li>Automated reports with R and R Markdown, saving 60+ hours of manual data entry per month</li>\n</ul>"}}]}}}