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Jhansi Bendi
Senior Software Engineer specializing in cloud-native microservices and event-driven systems
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About
Senior engineer/tech lead with 18+ years building large-scale distributed applications, specializing in performance and reliability improvements. Recently owned multiple apps on an email personalization team, shipping major optimizations (including a push-update feature and audience-count architecture redesign) that reportedly lifted system performance from ~50% to ~99% while also leading code standards, reviews, and mentoring.
Experience
Education
Key Strengths
- Improved push job/application performance from ~50% to ~99% via 'push light' update flow and downstream collaboration
- Rapidly redesigned and implemented audience count architecture (delivered in ~3 days) to handle complex rules and reduce timeouts
- Deep production troubleshooting (Hikari connection pool/DB connection set issues) to resolve timeout errors
- Strong code quality leadership: enforces coding standards, SOLID principles, PR review/merge discipline, and pairs on reviews
- Player-coach who remains highly hands-on (reported 90% coding / 10% management) while leading delivery and technical depth each sprint
- Reliability ownership: handled data corruption incident using DB snapshot replication and delivered permanent fix by correcting stored procedure logic
- Onboarding and performance coaching through KT, documentation, 1:1s, and pair programming to increase team contribution
- Built and shipped an AI-driven beauty routine/personalization service with ~10% sales lift in first two weeks
- Designed and implemented backend APIs integrating ML recommendations and order tracking via Kafka
- Pragmatic architecture tradeoffs (switched from data lake to MySQL to reduce latency for simpler datasets)
- Scaled order processing by introducing Kafka to eliminate order delivery losses to WMS
- Production reliability ownership: analyzed 6 months of missed tracking data, categorized errors, automated email reporting, and drove errors to zero
- Thorough scenario/edge-case analysis and test coverage for ambiguous personalization/banner logic changes
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