SDE@AWS Redshift | Distributed Systems | AI Infra | Computer Vision
I’m a software engineer with experience building and operating large-scale backend systems in production. I enjoy turning repeated, manual workflows into dependable automation and tooling, and I care about correctness, performance, and making systems easier to run over time.
Build the first automated Anomaly detection alarm, reduce risk detection from 2 months to 1 week.
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Improved large-scale test migration automation by enhancing the Jenkins-to-Hydra Migration Tool (JMT), raising automated migration success rates from ~20% to 80–90% and enabling self-service test migration across multiple Redshift teams.
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Owned system-level Vacuum system testing by developing and maintaining Kitchen Sink system tests across provisioned and serverless clusters, identifying 30+ defects and catching 7 production-level regressions pre-release that unit tests could not detect.
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Resolved critical stability and release risks by delivering 20+ patch- and release-blocking fixes, including crashes, assertion failures, and concurrency-related bugs, improving patch reliability and operational confidence.
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Supported SEV-2 customer incidents by providing Vacuum-specific debugging, log analysis, and RCA guidance, accelerating triage and reducing operational risk for large production workloads.
Selected for a highly competitive Fellowship designed to uplevel software engineering knowledge and skills through individualized curriculum to target growth areas and personalized coaching from industry leading software engineers.
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Completed intensive training to master DSA and practical CS topics through independent projects, pair-programming, and small mentor-led groups.
