Niyat Patel

About Niyat Patel

Senior Software Engineer with 7+ years working on large-scale distributed systems, backend services, and cloud infrastructure across Amazon Ordering (core checkout), Yahoo’s analytics platform, and high-growth startups. At Amazon, I focus on reliability, performance, and cost efficiency at 200K+ TPS scale—building an MCP (Model Context Protocol)- powered service resource analyzer that cut Ordering compute spend, designing traffic-priority and anti-bot algorithms that prevented $3.8M in losses and 170K+ dropped orders, and scaling a stress-testing system to 220K TPS using production traffic replay.Earlier, at Yahoo, I helped operate and optimize an 800+ node Apache Druid cluster serving 1M+ analytics apps and upgraded deployments with safer CI/CD pipelines. I’ve also built full-stack features, dashboards, and GraphQL APIs at startups. Day to day, I work mostly with Java, AWS, microservices, distributed systems, observability, performance tuning, and LLM/AI-driven developer tooling (MCP, agentic workflows, RAG). I enjoy owning ambiguous problems end-to-end and building systems that are reliable, efficient, and easy for other engineers to work with- Languages: Java (primary), Python, Node.js, JavaScript (ES6), SQL, Shell Script- Backend & Architecture: Distributed systems architecture, system design, microservices, REST APIs, event-driven design (Kafka), caching, high-availability, performance optimization (200k+ TPS)- Cloud & Infra: AWS (EC2, EKS/ECS, S3, DynamoDB, SQS/SNS, Lambda, CloudWatch), Kubernetes, Docker, Linux, Infrastructure-as-Code (Ansible, CloudFormation / Terraform), observability (metrics, logging, tracing)- Data & Storage: SQL & NoSQL, Apache Druid (OLAP), Apache Spark, Apache Kafka, data modeling & partitioning, query optimization & indexing, database performance tuning- Testing & Delivery: CI/CD (Screwdriver,[Jenkins/GitHub Actions]), load & performance testing, traffic replay, canary & gradual rollouts, regression automation- AI & LLMs: Large Language Models (LLMs), LLM tooling & integration (MCP, tool-calling), RAG pipelines, agentic workflows, prompt engineering, using LLMs for infra optimization/testingContact: n••••••••@gmail.com

Experience

1. Software Development Engineer Ii

   Amazon

   Sep 2021 — Present · San Francisco, CA, US

   Enhancing Amazon customers’ ordering & checkout experience- Ensuring availability of Amazon’s core checkout services by developing tools to stress test for high velocity events like Black Friday, Prime Day, Diwali- Optimizing customer experience by developing algorithms to prioritize important requests & throttle lesser important requests like bots- Buildig inbound & outbound traffic-priority algorithms in the core Ordering service shielding 60+ critical downstream services to detect hot-SKU (ex: PS5) spikes and throttle bot traffic to protect inventory, prevent promotions fraud, and prioritize real customers; preventing recurrence of $3.8MM losses in revenue and 170K+ dropped orders in prior peak shopping event - Prime day ‘23- Scaled a low-TPS regression tool to a distributed stress testing execution tool enabling up to 220k TPS for peak event readiness; uses recorded prod-traffic replay with selective API stubbing of statefuldependencies to prevent unintended production writes.

Education

• L.D. College of Engineering

  Bachelor's, Information Technology

  2012 — 2016

• San José State University

  Master of Science - MS, Computer Software Engineering

  2017 — 2019

Skills

• Python
• Apache Spark
• Amazon Web Services (Aws)
• Business Intelligence
• C++
• Php
• Cascading Style Sheets (Css)
• React Native
• Scala
• Linux
• Google Analytics
• Css
• Jquery
• Big Data Analytics
• Wordpress
• Negotiation
• Data Mining
• Cloud Computing
• Java
• Html
• Hadoop
• Html5
• Network Administration
• Javascript
• Network Security
• Critical Thinking
• C