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Raman Khattar

@ramankhattar

Software Engineer at Amazon who built an LLM-powered gift recommendation engine generating over $500M in gift purchases.

Germany

Message

At Amazon, I built an LLM-powered recommendation engine for Gift Finder, designing its training pipeline and integrating it across multiple Amazon pages. It generated over $500M in gift purchases.

I also led Rufus AI integration for gifting and designed cloud-native microservices and data pipelines. Previously, I built messaging services and a push notification system for Microsoft Kaizala, and created a packing optimization algorithm at Flipkart that reduced shipping costs by 40%.

Experience

Work history, roles, and key accomplishments

Current

Software Engineer

Current

Amazon

Mar 2021 - Present (5 years 7 months)

Technical lead for Gift Finder, a search and recommendation platform. Built an LLM-powered recommendation engine and led integration of AI chatbot Rufus for gifting use-cases, generating over $500M in gift purchases.

Kotlin Java Spring Boot AWS Lambda DynamoDB Amazon SQS S3 LLM Search Recommendations A B Testing Microservices Data Pipelines

Software Engineer

Microsoft

Sep 2016 - May 2020 (3 years 8 months)

Full-stack engineer for Kaizala, a chat-based enterprise app. Designed scalable backend services, built cross-platform push notification system in C++, and implemented monitoring and fault-tolerant messaging pipelines.

C++Android iOS Push Notifications Monitoring Diagnostics Fault Tolerance CI CD Testing Automation

Software Engineer

Flipkart

Jul 2013 - Aug 2016 (3 years 1 month)

Backend engineer for supply chain systems using Ruby on Rails. Created packing optimization algorithm reducing shipping costs by 40%, designed inventory reconciliation system, and led warehouse automation deployments.

Ruby on Rails REST APIs Algorithms Inventory Systems Warehouse Automation Logistics Ecommerce