Sep 2024 – Jul 2025 · 10 mos · Noida, Uttar Pradesh, India · On-site

• Adding copilot features in PPT. Added speaker notes to the deck, working on intelligent formatting of the deck etc

Nov 2021 – Aug 2024 · 2 yrs 9 mos · Noida, Uttar Pradesh, India · On-site

• At Microsoft Fluid Framework, I contributed to enhancing real-time collaboration through the development of scalable and performant table components. (https://github.com/microsoft/FluidFramework)
• Isomorphic Tables: Enabled server-side loading and headless operation of tables, facilitating efficient CRUD operations and maintaining real-time collaboration.
• Number Summary Component: Created a robust component to generate various numerical statistics based on columnar data, enhancing data insights.
• Performance Optimization: Improved table load times by 22%, significantly reducing user wait times and accelerating time-to-first-content.
• Scalability Enhancements: Spearheaded storage layer architectural changes to enable table scaling to thousands of rows, reducing load times and user actions to milliseconds.

Jul 2022 – Jan 2024 · 1 yr 6 mos · Noida, Uttar Pradesh, India

• I teach High level System design and DSA at Scaler

Jan 2022 – Jul 2022 · 6 mos · Noida, Uttar Pradesh, India

Apr 2022 – Nov 2023 · 1 yr 7 mos · Noida, Uttar Pradesh, India

• On my channel, I post videos on DSA solutions, leetcode contents and interview experiences. I will also be sharing some content on system design which I generally discuss in 1:1 sessions (Delayed because of my laziness 😜)
• Channel link - https://www.youtube.com/channel/UCUz0NKpGB0vJL5Pqm9GetvA

Dec 2021 – Apr 2023 · 1 yr 4 mos · Noida, Uttar Pradesh, India · Remote

• Mentoring people in getting better jobs
• Mock interviews
• 1:1 doubt clearing sessions on various topics like LLD, HLD, etc.

Jan 2019 – Oct 2021 · 2 yrs 9 mos

• Windows Client Development and Microservices Architecture:
• 1. Windows Client Features:
• Implemented signal handling to capture and process signals generated within Adobe products, enhancing crash detection and diagnostics.
• Introduced sandboxing support, enabling secure, containerized operation via IPC (Inter-Process Communication).
• Designed and developed a throttling mechanism on the client-side to manage backend pipeline load efficiently.
• Created a new, user-friendly UI that allows users to submit crash reports to Adobe for more detailed analysis.
• Optimized the transmission of log and dump data, reducing crash detection time and improving visibility on Adobe's crash dashboard.
• 2. ARM64 Support:
• Successfully released the Windows client for ARM64 architecture, expanding support across more platforms.
• 3. Cross-Team Collaboration:
• Worked closely with external teams and partner companies to provide seamless crash handling solutions that integrate with our client.
• 4. Microservices Development:
• Developed new microservices to handle a high volume of incoming requests from various clients, ensuring scalability and efficiency.
• 5. Backend Optimization & Microservice Architecture:
• Collaborated with Microsoft to resolve issues related to Win32 APIs, improving system stability and performance.
• Optimized backend components by reducing database connections, resulting in improved efficiency and faster processing.
• Re-architected the backend pipeline to be REST-compliant and follow microservice principles, enhancing system flexibility and scalability.
• 6. Adobe Content Logs Project 2.0:
• Led the integration of SQS (Simple Queue Service) for backup queuing of events, ensuring reliability and fault tolerance.
• Conducted cost optimizations by fine-tuning container usage, CPU, and memory allocation for optimal resource utilization.

Jan 2016 – Jan 2019 · 3 yrs

• Windows Crash Reporter Client and Backend Optimization:
• 1. Adobe Windows Crash Reporter Client:
• Delivered the Adobe Windows Crash Reporter client from the ground up, enabling the detection of crashes within Adobe products on users' machines.
• Intercepted various crash types (e.g., in-app crashes, heap corruption) in real time.
• Generated crash reports with critical metadata (e.g., crash stack, incident details).
• Captured memory dumps for in-depth analysis.
• Developed a user interface to request user consent for crash data submission.
• Displayed real-time solution URLs to guide users in resolving their issues.
• Single-handedly launched the client within one month, alongside major backend pipeline updates, ensuring integration across core Adobe products, including Photoshop, Illustrator, and InDesign.
• 2. Backend Optimization:
• Achieved an 80% reduction in bandwidth and storage requirements on the backend pipeline, cutting down storage from 100TB to 20TB. This optimization resulted from handling the increase in crash data (memory dumps and crash stacks) from the new Windows client.
• 3. Crash Data Processing Enhancement:
• Redesigned the backend pipeline to handle crash data from the new Windows client, reducing processing time from 15 minutes to 2-3 seconds per crash, improving real-time diagnostics.
• 4. Crash Reporting for Product Teams:
• Developed backend logic to present crash data to product teams, segmented by major releases (e.g., Max releases). This feature provided a comprehensive overview of crashes across all Adobe products, categorized by timeframes (minute, hour, day, week, month), enabling better issue tracking and resolution.

Jul 2014 – Jan 2016 · 1 yr 6 mos

• Full-Stack Developer – Adobe Crash Reporter:
• 1. Crash Reporter Tool Development:
• Actively contributed to the Adobe Crash Reporter as a full-stack developer, working on over 10 components across 5 technologies.
• Crash Reporter collects, analyzes, and maintains crash reports for Adobe products on Windows and macOS. It enables crash bucketization, similarization, and resolution, offering product teams valuable insights for prioritizing fixes and stabilizing products.
• 2. Crash Reporter Dashboard:
• Developed major features of the Crash Reporter dashboard, leveraging AngularJS and the Spring framework to enhance user experience and functionality.
• 3. Database Optimization:
• Designed and updated the database schema to support new features introduced in the dashboard, optimizing queries for significant performance improvements.
• 4. Miscellaneous Tasks:
• Migrated the Windows resolver from Perl to Java, improving maintainability and performance.
• Resolved runtime (Dalvik) update issues in the Crash Reporter Android client, ensuring smoother updates.
• Implemented custom crash bucketization to categorize crashes based on threads other than the crashing thread, offering better granularity in crash data.

Jan 2014 – Jun 2014 · 5 mos

• Creative Cloud User Recognition and Settings Synchronization:
• Designed and implemented a seamless user recognition system for Adobe Creative Cloud based on facial recognition technology.
• Developed a solution that automatically registered and recognized users, ensuring their system and application settings were consistently maintained across multiple machines and devices without any user intervention.
• Enabled users to log in to new devices, where the system would automatically recognize them and synchronize their settings from the cloud.
• Ensured real-time updates to system and application settings, which were instantly preserved in the cloud for consistency across all devices.
• Integrated facial recognition data with the user's Adobe account, creating a transparent and frictionless experience for users while maintaining security and personalization.

Sep 2014 – Jun 2015 · 9 mos · Noida, Uttar Pradesh, India

• A classroom program where college students/ professionals were trained for interviews of top tech giants.