Headline

Backend Engineer @ Fibe | Building scalable fintech systems | Java · Spring Boot · AWS · Microservices | NIT Kurukshetra

About

Hey! I'm a backend engineer who's spent the last 3 years building the guts of a fintech lending platform at Fibe — everything from a real-time decision engine to KYC/fraud detection systems. I like owning things end-to-end. Some stuff I've built: a decision engine that cuts latency from 1s to 52ms, a GenAI-powered selfie liveness detection system for KYC, and the architecture behind how Fibe tracks loan applications — so customers can switch between loan products mid-application without losing their progress. Core stack: Java, Spring Boot, AWS, Redis, MySQL, microservices. Also big into using AI tools (Copilot, Claude) to move faster as a dev — it's genuinely changed how I work day to day. Outside of work, I've got a competitive programming streak — ICPC and CodeChef rankings — and I studied at NIT Kurukshetra. Currently exploring new opportunities — always happy to connect! Feel free to reach out on pgoyal0512@gmail.com

Location

Bangalore Urban

AI stack

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Work experience

Software Engineer at Fibe.India (Formerly EarlySalary), Sep 2023 - Present · 3 yrs, Pune District, • Leading backend engineering for Fibe's Core LOS (Loan Origination System) — owning KYC, VKYC, LAMF (Loan Against Mutual Funds), and decision modules across a high-throughput lending platform. • Architected a real-time LOS Decision Engine (AWS Lambda, AppConfig, Redis) — reduced P99 decision latency from 1s → 52ms via read-through caching, enabling no-code journey configuration. • Owned the complete KYC module — integrated VKYC providers (HyperVerge, IDFY, Digilocker), built a Credit Information Report module with CIBIL & Equifax, and architected the eKYC Setu (NPCI/UIDAI) backend with secure Aadhaar authentication. • Delivered LAMF (Loan Against Mutual Funds) end-to-end — integrated 3 financial data providers and established a new lending vertical, achieving ₹20 Cr+ in disbursals within 6 months. • Engineered a Feature Management System that cut deployment failures by 75%, and hardened LOS reliability by reducing bot exceptions ~95% (1,000 → <50/day). Stack: Java · Spring Boot · AWS (Lambda, AppConfig, Secrets Manager, S3, CloudWatch) · Redis · MySQL · MongoDB · DynamoDB · Microservices · REST APIs

IoT / AI Intern at DS Group, Jan 2022 - Jun 2022 · 6 mos, Noida, Uttar Pradesh, India, Research work in AI on Time Series Forecasting. Solved Real world problems. Made an SMS based device controliing application using IoT Communication Protocols.

Education

B. tech, Information Technology, National institute of technology kurukshetra