Yogesh Muppiri
Software Development Engineer | Amazon
Building resilient distributed systems that power global scale, production reliability, and measurable business impact.
About Me
I am an experienced Software Development Engineer specializing in architecting secure, scalable backend systems and high-availability microservices. With a Master's in Business Analytics and Artificial Intelligence from UT Dallas, I seamlessly bridge the gap between advanced AI capabilities and robust, enterprise-grade infrastructure.
My engineering focus spans across developing complex authentication flows, orchestrating containerized deployments, and automating infrastructure with Terraform and CI/CD pipelines. Leveraging languages like Java and Python alongside extensive AWS cloud resources, I am passionate about building reliable, fault-tolerant software that drives real-world impact at an extreme scale.
Experience
Software Development Engineer
July 2025 - PresentAmazon | Seattle, WA
- Engineered extreme-scale infrastructure at Amazon, supporting 100B+ global memberships and building highly distributed backend systems.
- Architected high-throughput Generative AI and backend evaluation pipelines capable of processing 27M+ product assessments per second with optimized compute efficiency.
- Designed and scaled a tier-1 authentication gateway system (Helis) serving 300+ internal clients, implementing secure API mediation and zero-trust protection mechanisms.
- Built and optimized Coral-based throttling using a token bucket algorithm to mitigate burst traffic and protect downstream services from update storms.
- Managed and optimized 3M+ active selection rules, ensuring precision-based filtering and highly scalable data flow across distributed microservices.
- Contributed to multi-region deployment across 6 global regions for a 1M+ TPS service, achieving p99 latency of 150ms through performance tuning and resilient architecture design.
- Optimized high-volume membership lookup workloads by introducing an in-memory caching architecture with S3 storage fallback, reducing infrastructure costs and improving latency for millions of daily API calls under extreme-scale traffic conditions.
AI/ML Engineer
March 2024 - Feb 2025Community Dreams Foundation | Orlando, FL
- Enhanced LLaMA 2 performance on Groq's infrastructure by integrating RAG pipelines in AWS SageMaker,improving contextual accuracy by 30%.
- Engineered an AI-driven screening system using LLMs (Gemma 2, LLaMA 2), increasing shortlisting accuracy by 35%.
- Deployed ML models on AWS with Terraform, configuring EC2, NAT Gateway, and Route 53; automated evaluation using CloudWatch, reducing hiring time by 25%.
- Created a real-time AI system to analyse interview responses and visualize actionable insights with Matplotlib, reducing assessment time by 40% and improving selection accuracy.
Technical Skills
Programming Languages
Backend & Systems
Cloud & AWS
AI / ML
Academic Projects
Knowva AI
AI & LLM ApplicationAI-Powered Document Intelligence & Medical Q&A Assistant
- A full-stack LLM application combining retrieval-augmented generation (RAG), FAISS vector indexing, and LangChain pipelines to intelligently parse multi-modal formats (PDF, DOCX) and cut manual review time by up to 80%.
- Architected with a custom Streamlit frontend and powered by highly scalable NVIDIA NIM and OpenAI APIs, featuring robust prompt chaining, real-time inference, and a specialized Medical Q&A Assistant.
Walmart Data Analysis
Data Science & MLConducted a comprehensive analysis of North American Walmart store sales data to identify key influencing factors such as holidays, fuel prices, weather variations, and unemployment rates.
Executed meticulous data cleaning pipelines and applied sophisticated machine learning models, including Random Forest and Decision Trees, to derive actionable insights for strategic decision-making.
Demonstrated the critical economic footprint of these stores, highlighting how stable sales performance prevents local unemployment and bolsters community well-being through essential tax revenue.
AI Fundamentals? (just in 15 minutes!)
Take a quick dive into the mechanics of Machine Learning, LLMs, and Foundation Models. No fluff, just the core engineering concepts.
Read the 15-Min BreakdownCertifications
Certified Cloud Practitioner
AWS
Azure Administrator Associate
Microsoft
Python for Data Science, AI & Development
IBM
Machine Learning for All
University of London
Software Development Processes & Methodologies
University of Minnesota
Research Publications
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Detection of Cyber-attacks using Machine Learning technique
Peer-reviewed Research
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Diabetes Prediction using Ensembling Methods in Supervised learning
Peer-reviewed Research
Volunteering & Leadership
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Event Coordinator
GUSAC - GITAM University Science and Activity Centre
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NSS Member
UPES
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Member
Indian Red Cross Society (National Headquarters, New Delhi)
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Teaching Assistant
GITAM Deemed University
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Programming Officer
Association for Information Systems
Creative Pursuits
When I'm not writing code or analyzing data, I step away from the screen and capture life through a lens. Check out my photography portfolio.
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