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Amazon

Software Development Engineer Intern

May 2025 - August 2025
Seattle, USA

End-to-End Search Query Classification System

Implemented a comprehensive search query classification system to fetch and normalize 50,000 search queries from database, applied LLM prompt templates via Python script to categorize queries into distinct categories, and stored results in Amazon S3.

PythonLLMAmazon S3JavaSpring BootSQL

📋 Project Overview

Implemented a comprehensive search query classification system to fetch and normalize 50,000 search queries from database, applied LLM prompt templates via Python script to categorize queries into distinct categories, and stored results in Amazon S3.

✨ Key Highlights

Fetched and normalized 50,000+ search queries from database using SQL

Applied LLM prompt templates for intelligent query categorization

Stored classifications in Amazon S3 for scalable access

Implemented caching mechanism using HashMap data structure for classification-aligned query execution

Achieved precise category-specific query results using Java Spring Framework

🛠️ Technology Stack

PythonLLMAmazon S3JavaSpring BootSQL

🏗️ System Architecture

System Components

Query Fetcher

Fetches and normalizes search queries from database

SQL

LLM Classifier

Applies LLM to categorize queries

PythonLLM API

S3 Storage

Stores query classifications

Amazon S3JSON

Cache Layer

In-memory cache using HashMap data structure

HashMapJava

Query Executor

Executes category-specific queries

JavaSpring Boot

Data Flow

Query FetcherLLM Classifier

Sends normalized queries

50K search queries
LLM ClassifierS3 Storage

Stores categorized queries

Query + Category mappings
S3 StorageCache Layer

Loads classifications

Category data
Cache LayerQuery Executor

Provides cached classifications

Classification results

Architecture Flow

Query Fetcher

LLM Classifier

S3 Storage

Cache Layer

Query Executor

🔄 End-to-End Flow

Step 1:Query FetcherLLM Classifier

Sends normalized queries

50K search queries
Step 2:LLM ClassifierS3 Storage

Stores categorized queries

Query + Category mappings
Step 3:S3 StorageCache Layer

Loads classifications

Category data
Step 4:Cache LayerQuery Executor

Provides cached classifications

Classification results

📊 Component Details

Query Fetcher

Fetches and normalizes search queries from database

SQL

LLM Classifier

Applies LLM to categorize queries

PythonLLM API

S3 Storage

Stores query classifications

Amazon S3JSON

Cache Layer

In-memory cache using HashMap data structure

HashMapJava

Query Executor

Executes category-specific queries

JavaSpring Boot

🎯 Impact & Results

1

Fetched and normalized 50,000+ search queries from database using SQL

2

Applied LLM prompt templates for intelligent query categorization

3

Stored classifications in Amazon S3 for scalable access

Kushal Adhyaru - AI/ML Engineer & Full-Stack Builder