# Kartik Chhapia > Senior Software Engineer @ LinkedIn Location: San Francisco Bay Area, United States Profile: https://flows.cv/kartikchhapia Visionary Senior Software Engineer with 8+ years architecting and leading the delivery of scalable, mission-critical distributed systems, microservices, and cloud-native platform. Deep expertise in container orchestration, CI/CD strategy, event-driven systems, performance optimization, and data modeling. Proven leader driving complex, cross-functional projects end-to-end, mentoring engineers, collaborating with product managers, and influencing technical direction for high-performance systems. ## Work Experience ### Senior Software Engineer @ LinkedIn Jan 2025 – Present | Sunnyvale, CA Driving job poster growth and engagement at LinkedIn by architecting high QPS backend entry points and onboarding flows. Engineering efforts focus on the member eligibility engine and real-time banner services that dynamically target potential employers, ensuring low latency response times for millions of top of funnel acquisition events. These systems serve as the front door for employers, balancing complex targeting logic with the performance requirements of a high traffic ecosystem. Designing and operating nearline notification pipelines using Apache Beam, Flink, and Kafka to re-engage users at high intent moments such as abandoned drafts and lifecycle milestones. These event driven systems power automated, high volume outreach across email, push, and in-app channels via LinkedIn’s Air Traffic Control system. By leveraging stream processing, these pipelines turn real time user actions into meaningful engagement opportunities that help employers complete their hiring journey. ### Software Engineer @ GSOBA Jan 2025 – Present ### Senior Software Engineer @ Cisco Jan 2022 – Present | San Jose, California, United States ### Software Engineer @ Cisco Jan 2020 – Jan 2022 | San Francisco Bay Area Contributed to the development of the Webex Experience Management (XM) microservice, enabling organizations to send surveys and collect customer feedback through robust, scalable microservices architecture. Utilized Java, Spring Boot, and Maven for backend development, ensuring modularity, maintainability, and scalability of the solution. Designed and implemented RESTful APIs for Questions, Answers, and Reports, facilitating seamless integration and data flow between the microservice and the MongoDB database. Ensured data consistency, reliability, and high availability by applying best practices in database design and API development. Leveraged Docker for containerization, facilitating consistent testing and deployment across multiple environments (CI/CD pipelines). Employed Agile methodologies in collaboration with cross-functional teams to iterate rapidly, ensure code quality, and meet evolving business requirements. Successfully rolled out the solution across global regions, including the US, EU, Canada, Japan, Australia, and New Zealand, onboarding 150+ organizations and enhancing user experience and customer satisfaction. ### Software Engineer @ Amazon Jan 2019 – Jan 2020 | Seattle, Washington, United States Contributed to the Log Analytics tool, a web application for publishing failure metrics, optimizing SQL queries and improving code structure to significantly enhance performance and scalability. Implemented concurrent SQL reads from the AWS RDS (Relational Database Service), reducing data retrieval time from over 30 minutes to a few seconds, ensuring better performance and user experience. Added new features including live order status tracking and business-friendly error messages, improving the overall functionality and usability of the tool. Worked on the IMEI project, an initiative for Amazon.in sellers to enter serial numbers for items they sell, integrating backend services and UI development for seamless user interaction. Developed mobile and web applications, implementing serial number validation checks and redesigning API calls for improved data validation and efficiency. Collaborated with senior engineers to document system design changes, ensuring proper technical documentation and smooth implementation of architectural modifications. ### Machine Learning Intern @ Fidelity Investments Jan 2018 – Jan 2018 | Greater Boston Area ### Data Scientist Intern @ Burning Glass Technologies Jan 2017 – Jan 2017 | Greater Boston Area Implementing a Deep Neural Network Classifier that can perform a word sense disambiguation on words present in a job posting and can predict whether the "skill sense" of the word is present in the job text or not. More specifically, the model will be able to distinguish between those job texts in which the word"excel" refers to the skill of using Microsoft Excel and not the "verb sense"of the word excel (excel at sports etc). This is a significant overhaul of the current manual and tedious process of tagging a job post with a skill. The model will substantially reduce the time an analyst will spend in generating rules for tagging job texts with skills and will also improve the recall of the number of job texts that are tagged. I am also implementing a neural network model that can perform a skill entity recognition on the text of a job posting and identify new skills that aren't present in the skill corpus. ### Natural Language Processing Intern @ Fidelity Investments Jan 2017 – Jan 2017 | Boston, Massachusetts Developed a platform to identify macro-economic research articles from a set of all articles that are published by various analysts in the company. This system significantly lowered the amount a time portfolio managers and economists spend in reading research. The naïve bayes model and convolutional neural networks (CNN) were two techniques used to perform this task and Python and TensorFlow were used to implement the code. This project was selected for presentation at the NABE Tech Economics Conference in Seattle. ### Design Verification Engineer @ Arrow Devices Jan 2013 – Jan 2015 | Bengaluru, Karnataka Backend software engineer designing large scale distributed systems using Java. ### Research Assistant @ Hewlett-Packard Laboratories Jan 2012 – Jan 2012 Developed a system which used the voice of a Speaker for verification purposes. It was trained and tested using Gaussian Mixture Models and implemented in C++. An accuracy of 90% was achieved on a set of 500 Speakers. ## Education ### Master of Science (MS) in Computer Science University of Massachusetts Amherst ### Bachelor of Engineering (BEng) in Electrical and Electronics Engineering Birla Institute of Technology and Science, Pilani ### Bombay Scottish School ## Contact & Social - LinkedIn: https://linkedin.com/in/kartik-chhapia --- Source: https://flows.cv/kartikchhapia JSON Resume: https://flows.cv/kartikchhapia/resume.json Last updated: 2026-04-10