Architected and built a highly scalable observability data pipeline from inception, enabling real-time processing and analysis of massive telemetry datasets while maintaining low-latency performance across distributed systems
Led end-to-end service architecture and development as founding engineer, designing multiple microservices from the ground up to establish core platform infrastructure and scalable system foundations
Drove early-stage technical decisions and platform strategy, establishing architectural patterns, technology stack selections, and engineering best practices that enabled rapid product development and team scaling
Delivered foundational data processing capabilities, creating robust pipeline infrastructure that handles high-volume observability data ingestion, transformation, and routing with enterprise-grade reliability
Senior Software Engineer
Rubrik
02.2021 - 01.2022
Designed and maintained a distributed job scheduling framework that orchestrates execution of critical cluster operations across Rubrik's data management platform, ensuring reliable task coordination and resource optimization
Resolved customer-reported defects and production issues through systematic debugging, root cause analysis, and code fixes, improving system stability and customer satisfaction
Collaborated on system architecture and code quality initiatives by conducting thorough code reviews and participating in design reviews to ensure scalable, maintainable solutions
Contributed to platform reliability and performance by proactively identifying, troubleshooting, and resolving bugs throughout the codebase while maintaining high coding standards
Member of Technical Staff
VMWARE INC.
06.2018 - 02.2021
Contributed to the development of a VMware Secure State - a product that monitors cloud environments for configuration related security threats.
Developed multiple features in a microservice-driven backend data pipeline. Some highlights - a microservice to transform an API response to a graph model, a generalized rate-limiting framework to restrict the number of events processed, a graph-based data cleanup feature to ensure an accurate experience for our customers.
Experience working with cloud services in AWS such as SQS, Kinesis, S3, DynamoDB, Neptune, ElasticSearch and Elasticache.
Collaborated with customers in order to understand use cases and prioritize feature development - assisted onboarding the first ~1200 Azure cloud accounts on the platform.
Served as team lead - organized, communicated, and coordinated milestone objectives and on a more granular level, sprint goals with product team for several sprints.
Played an active role on the team through the product life cycle from pre-alpha to public release.
Teaching Assistant
University of Illinois, Urbana-Champaign
01.2017 - 05.2018
Assist students in building robust applications involving concepts such as MVC, version control, mobile development and API design.
Research Intern
NETRADYNE
05.2017 - 08.2017
Developed an Active Learning framework for continuous training of an object detection model.
Trained a binary classifier capable of identifying a scheme of images (for example, potential false negatives). This allowed a more focused approach towards labelling new data.
Developed visualizations in order to understand how to improve our object detection model.
AI Training Specialist at Practical AI Academy (formerly Asia Applied AI Academy)AI Training Specialist at Practical AI Academy (formerly Asia Applied AI Academy)