May 2024 – Aug 2024 · 3 mos · Mountain View, California, United States · Remote

• Acquired by Fortinet
• Provided on-call support to approximately 1500+ customers, bringing in around 100M in ARR.
• Owned design and development of an alert details UI and API, providing users with additional context and information about security alerts. This initiative reduced the mean time to investigate (MTTI) by 65%.
• Led the migration from Codefresh to GitHub Actions (GHA), resulting in build times that were 3X times faster for all team-owned services.
• Developed a Python service for running a CLI to manage alert throttling, reducing false positive spikes by thousands, thus enhancing internal developer efficiency and minimizing erroneous alerts sent to customer environments.
• Executed unit tests, integration tests, and canary tests by employing frameworks such as Jest, JUnit, Cypress etc.

Jan 2023 – May 2024 · 1 yr 4 mos · Mountain View, California, United States · Remote

• Contributed to the end-to-end security alerting system integral to Lacework’s (Sutter Hills and Google Ventures backed startup to be acquired by Fortinet) Cloud Native Application Protection Platform (CNAPP), utilizing technologies like React, Typescript, Java and GoLang, within a microservice architecture.
• Integrated MITRE ATT&CK tags into the UI, enhancing users’ understanding of the threat landscape, improving security posture, and enabling more effective detection and response strategies.
• 30% increment was observed in user interaction of alerts after the introduction of this feature.
• Collaborated with cross-functional teams and fostered a culture of continuous improvement by taking feedback and delivering quality code (with good test coverage) with high bars.
• Developed a low-latency pipeline for threat intelligence alerts, cutting processing time from 90-120 minutes to under 5 minutes (P95 latency). Contributed significantly to UI improvements and query optimization for database operations.

May 2022 – Aug 2022 · 3 mos · Seattle, Washington, United States

• Facilitated full stack project by adding new view player profile feature and two other updates in screens/ functionalities with the ”Fantasy Games” team in Facebook App (impact to 80 Million users).
• Newly introduced player profiles led to a 25% increase in UI interaction from the game home.
• Proposed and executed plan to add pagination with new UI in screens having huge data to improve app performance by 30%.
• Simplified and refactored code to make functions and database queries generic, enhancing readability and improving performance by 7% for millions of users.
• Completed the intern project, met stretch goals, and handled extra tasks, earning an exceeding expectations rating.

Jan 2022 – May 2022 · 4 mos · California, United States

• Designed, implemented and maintained large distributed React-based applications and micro-services.
• Took ownership of optimizing 2 features to enhance interactivity, working with a team of five including UX.
• Worked directly with customers to propose and created new screen designs for user screens requested by 75% of users

Sep 2021 – Dec 2021 · 3 mos · San Jose, California, United States

Feb 2020 – Apr 2020 · 2 mos

• Teaching Assistant in Course Fundamentals of Computer Programming

May 2019 – Jan 2020 · 8 mos

• Served IEEE Ahmedabad University student branch as web manager and committee member in organizing various IEEE Events by AU SB.

May 2019 – Dec 2020 · 1 yr 7 mos · Gandhinagar, Gujarat, India

• Transformed a concept into a production-ready web application for smart electric meters, enabling electricity usage analysis and home automation, resulting in up to 20% electricity savings through app monitoring.
• Optimized the UI using Redux with memoized selectors, achieving up to 90% performance improvement in rendering UI.
• Designed and developed a regional language block coding platform used by 1000+ high school students and teachers.

Jan 2019 – Apr 2019 · 3 mos · Ahmedabad, Gujarat

• Developed “Fashion Recommendation System” using machine Learning
• Algorithms, Data Analytics and Python Libraries. Unsupervised Learning (Clustering) was used to recommend Fashion clothes.