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Saurabh VaishSV
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Saurabh Vaish

@saurabhvaish

Backend Engineer building scalable distributed systems and data pipelines, blending Java/AWS with GenAI for fintech-grade reliability.

India
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What I'm looking for

I want to build reliable backend services and data pipelines on AWS and modern architectures, improving performance and scalability. I’m excited to apply GenAI/LLMs to automate development and accelerate delivery while partnering in strong Agile teams.

I’m a Backend Engineer with 5.5 years of experience designing and scaling highly-available distributed systems and data pipelines. I focus on delivering resilient backend services through strong Java expertise, AWS, and Agile collaboration, with a FinTech background in payments and security.

At Goldman Sachs, I engineered the migration of critical PnL report generation pipelines from on-premise to Snowflake cloud using Java. I orchestrate scheduler-based report generation and optimized API response time by 90% (10 min → under 1 min) through query restructuring and async job orchestration.

I also build automation that accelerates delivery—prototyping a Python reconciliation tool using Generative AI (GitHub Copilot) and integrating GenAI tools (Devin AI) into the development lifecycle. In parallel, I onboarded deposits to new flows, enhanced report generation on AWS, and refactored core functionality into reusable libraries across projects.

Earlier, at Razorpay, I developed integrated reconciliation systems and improved backend performance by 20% by extracting logic into microservices. I strengthened security by updating encryption protocols for Amazon Pay, improved report download time from 2 min to 30 sec using Kafka and multiple threads, migrated authentication to token-based with Spring Security and JWT, and reduced Sonar issues in middle-ware microservices by 95%.

Experience

Work history, roles, and key accomplishments

Razorpay logoRA

Product Development Engineer I

Jan 2022 - Apr 2024 (2 years 3 months)

Developed integrated reconciliation for user transaction data and improved transaction-processing backend performance by 20% by extracting code into a microservice. Reduced report download time from 2 minutes to 30 seconds using Kafka and multithreading, and migrated authentication from session-based to token-based with Spring Security and JWT.

Education

Degrees, certifications, and relevant coursework

Jaypee Institute of Information Technology logoJT

Jaypee Institute of Information Technology

Bachelor of Technology, Computer Science

2016 - 2020

Bachelor of Technology in Computer Science from 2016 to 2020 at Jaypee Institute of Information Technology.

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