Headline

Engineer @ Razorpay | Building Scalable Payment Solutions | SpringBoot, Kafka, Redis, Docker, Microservices, Kubernetes

About

Currently a Product Engineer at Razorpay, leveraging a Bachelor of Engineering in Computer Science from Chitkara University. Contributed to software development as an intern, bringing expertise in Go, PHP, and Python to enhance product capabilities. Collaborates on scalable solutions with a focus on cloud computing, supported by certifications from IBM and leading institutions.

Location

Greater Bengaluru Area

AI stack

antigravity

claude code

claude

codex

cursor

gemini

Work experience

Product Engineer at Razorpay, Aug 2025 - Present · 1 yr 1 mo, ◦ Decomposed Razorpay Routes (split payments & fund routing) from a monolith into modular Spring Boot microservices, lifting request throughput 30% and enabling zero-downtime deploys at millions-of-transactions daily scale. ◦ Engineered Razorpay Settlements services (merchant payouts & reconciliation) on a Kafka event-driven, Redis-cached architecture, orchestrating payout scheduling and ledger reconciliation while reducing settlement processing latency by 25%. ◦ Improved production observability for Routes and Settlements with 15+ structured log events, 8 service metrics, and 4 alerting dashboards, cutting P1 / P2 merchant-issue triage time by 35%. ◦ Built reusable validation and routing helpers across 4 split-payment modules, reducing duplicate service logic and accelerating API rollouts. ◦ Shipped LLM-powered agentic workflows (tool/function calling) that automate internal engineering ops, cutting manual intervention by 50% and on-call load by 40% across 3 team workflows.

Product Engineer Intern at Razorpay, Sep 2024 - Aug 2025 · 1 yr, ◦ Developed 6 backend APIs for Razorpay Offers (bank/card discount campaigns), supporting 3 campaign types, eligibility validation, and checkout-time discount application for merchant integrations. ◦ Raised Offers API test coverage to 85% by adding 40+ unit and integration tests across eligibility rules, discount calculations, and failure paths. ◦ Automated regression checks for 25+ Offers checkout scenarios, preventing campaign eligibility and pricing defects before the merchant launches. ◦ Resolved legacy data discrepancies in transaction records via a Python AI bot, saving 40% of weekly manual engineering hours.

Education

Bachelor of Engineering - BE, Computer Science, Chitkara University

Public links

github: https://github.com/keshav-47