Harsh Nagoriya

Backend Engineer

Harsh Nagoriya

About

Software Development Engineer II with expertise in building large-scale distributed systems, multi-agent AI platforms, and cloud-native microservices. At Amazon, I architect experimentation frameworks and AI-driven automation systems that operate across 18+ global marketplaces and directly drive Prime membership growth. Experienced in leading complex technical initiatives end-to-end - from system design through delivery - with a focus on scalability, operational excellence, and measurable business impact.

Experienced in designing and building large-scale distributed systems and microservices, with a focus on reliability, performance, and clean system boundaries across complex service ecosystems.

Skilled at taking ownership of ambiguous, high-impact problems - driving them from system design through production delivery with minimal oversight.

Strong cloud-native engineering background with hands-on experience building event-driven architectures, serverless systems, and infrastructure-as-code on AWS.

Effective cross-functional collaborator - experienced working across multiple teams to align on technical direction, unblock dependencies, and ship cohesive solutions at scale.

Experience

Software Development Engineer II

Amazon

Dec 2023 - Present Seattle, WA
  • Architected a core experimentation framework for a multi-agent AI system, designing autonomous workflows that intelligently generate hypotheses and execute targeted content experiments. Delivered this highly scalable infrastructure as a primary technical building block to drive a leadership objective of acquiring 1M+ new Prime members.
  • Led the system design and development of the orchestration layer for a multi-agent AI experimentation platform scaling across 18+ marketplaces, solving complex automation bottlenecks to drastically accelerate global marketing initiatives.
  • Designed and implemented a localization preview service integrated with Figma, automating conversion of design mocks into marketing assets and providing real-time validation of localized content; reduced global launch timelines from 8 weeks to 1 week.
  • Developed a distributed microservice to manage global rollout of Prime savings and benefits, automating audits and updates for 1,500+ marketing assets across 9+ marketplaces; reduced operational effort from 2 months to 1 day.
  • Led design and implementation of Prime's first member-retention A/B testing framework, building orchestration logic across 5+ teams and delivering statistically significant results with a projected uplift of 11,000+ annualized Members.
  • Owned end-to-end migration of an internal content management service from legacy NetScaler hardware to an AWS Application Load Balancer with zero downtime, eliminating critical security risks and enabling cloud-native scalability.
  • Built a real-time, event-driven data pipeline using AWS Kinesis, migrating a critical service off a deprecated platform and ensuring 100% business continuity for experiment analysis dashboards.
  • Drove key process improvements for the engineering team's sprint and operational excellence cadences, resulting in sustained 80%+ task completion rates and more efficient planning cycles.

Software Engineer

Audere

Aug 2022 - Dec 2023 Seattle, WA
  • Built serverless API components using AWS API Gateway and Lambda functions, supporting 10K+ daily requests with 99.9% uptime across production environments.
  • Developed 5+ REST endpoints with Python Lambda functions, handling data processing and API integration for 3 mobile applications.
  • Contributed to Infrastructure as Code using Terraform, automating deployment of AWS resources across dev/staging/prod environments.
  • Built automated database migration pipeline using Alembic, reducing schema deployment errors by 95% and saving 15+ hours of manual database management per week.
  • Integrated automated testing workflows into CircleCI pipelines, improving code quality and reducing manual testing overhead by 60% across development cycles.
  • Developed comprehensive Android test automation using Espresso framework, increasing test coverage from 45% to 70% and catching 85% of bugs before production deployment.
Dec 2020 - Apr 2021 Gandhinagar, India
  • Enhanced the development of Ethereum blockchain by utilizing Solidity, JavaScript, and Java and maintaining both client-side and server-side code. Complied with industry-standard software development procedures and crafted 5 UML diagrams to enhance comprehension and facilitate future maintenance.
  • Participated in code reviews to ensure the quality and reliability of the final product.

Skills

Languages

Java Python TypeScript JavaScript C++ SQL Bash

AWS

Lambda API Gateway Kinesis DynamoDB S3 SQS/SNS ALB Redshift CDK

Frameworks & Tools

Spring Boot Node.js React Docker Terraform Kubernetes Git

Concepts

Distributed Systems Microservices Event-Driven Architecture Large-Scale System Design Platform Engineering IaC

Education

Arizona State University

Arizona State University

Master of Science

(Computer Science)

August 2021 - May 2023

Relevant Coursework:

Cloud Computing, Data Processing at Scale, Software Testing/Quality Management, Data Visualization

Dharmsinh Desai University

Dharmsinh Desai University

Bachelor of Technology

(Information Technology)

August 2017 - May 2021

Relevant Coursework:

Data Structure and Algorithms, Databases, Advanced Java and Design Patterns, Distributed Computing

Academic Projects

Face Recognition on a PAAS

AWS Lambda, Amazon SQS, Amazon DynamoDB, Amazon API Gateway, Docker, RaspberryPI Mar 2022 - May 2022
  • Designed and implemented a distributed application using AWS Lambda, Amazon SQS, Amazon DynamoDB, and Amazon API Gateway to perform real-time face recognition on real videos recorded by IoT devices, resulting in a highly scalable and efficient system.
  • Utilized Docker to containerize the application and deploy it on an AWS Lambda, improving its portability and flexibility.
  • Tested the AWS Lambda function by sending over 500 requests in 5 minutes, identifying and resolving performance bottlenecks and improving the overall system responsiveness.

Face Recognition as a Service

Amazon EC2, Amazon SQS, Amazon S3, Flask Jan 2022 - Mar 2022
  • Constructed a face recognition service based on Python, deployed on AWS EC2, incorporating SQS and S3 for cost-efficient scaling.
  • Implemented manually scripted load-balancers that automatically scaled in and out on demand to accommodate changing traffic patterns.
  • Evaluated scalability by generating 1000 concurrent user requests, demonstrating ability to handle high volumes of traffic efficiently.

Soccer Tournament Website

Java Server Pages, Servlets, J2EE, JQuery, AJAX, Bootstrap, MVC, MariaDB Sep 2021 - Dec 2021
  • Developed a J2EE-based website with 6 distinct user roles using Agile principles, UML design concepts, and Git version control.
  • Ensured high-quality results through specification-based and structural-based testing.

Technical Papers

Live Facemask Detection System

International Journal of Imaging and Robotics™

2021 Volume 21, Issue I, Page No: 1-8, ISSN: 2231-525X

Attendance System using Face Recognition utilizing OpenCV Image Processing Library

International Journal for Research in Applied Science and Engineering Technology

2020 Volume 8, Issue VI, Page No: 1811-1814, ISSN: 2321-9653

DOI: 10.22214/ijraset.2020.6297

Live Helmet Detection System for Detecting Bikers without Helmet

International Journal of Knowledge Based Computer Systems

2019 Volume 7, Issue 2, Page No: 14-17, ISSN: 2321-5623

DOI: 10.5281/zenodo.4050483

Get In Touch

Let's connect and discuss opportunities to work together.