Hi, I'm Rutwik Patel
I build and ship software that people actually use — from enterprise data products to backend services, infrastructure, and AI-driven systems. I care about performance, reliability, and real-world impact (I wrote a Redis-compatible store in C++ that hits 984K+ ops/sec). USC MS Computer Science. Published IEEE researcher.
About Me
Software Engineer passionate about building scalable products and solving complex problems
Who I Am
I'm a Software Engineer and USC Master's graduate who works close to the systems layer — backend services, infrastructure, and applied AI — and enjoys making complex things fast and reliable.
At Sigma Computing I shipped four production features used by 60+ enterprise organizations, and optimized rendering of large data grids with memoization and virtualization. At World Salon I refactored a monolithic backend into modular payment and event services (cutting request latency by 20%), built OpenAI-powered pipelines that processed 58,000+ profiles end-to-end, and containerized and deployed everything on AWS with Docker, EC2, S3, and GitHub Actions.
As a Research Assistant at USC Marshall, I engineered fault-tolerant ETL pipelines and RAG semantic-search systems over 500GB+ of sustainability disclosures, indexing 2M+ data points in PostgreSQL for 30+ researchers.
For fun and depth, I build systems from scratch — like miniredis, a Redis-compatible in-memory store written in C++17 with a non-blocking epoll/kqueue reactor and a hand-written skip list, reaching 984K+ ops/sec.
I'm open to full-time roles in Software, Infrastructure, Backend, and AI Engineering. Happy to connect with engineers, founders, and recruiters.
Impact
GitHub Activity
Programming Languages
Frontend
Backend
Databases
Cloud & Infrastructure
AI / ML
* Proficiency levels are AI-estimated based on project experience, internship work, and research contributions.
Experience & Education
My professional journey and academic background
Work Experience
USC Marshall School of Business, Los Angeles, CA
Research Assistant
- •Built a RAG-based semantic search and chat platform over 10K+ vector embeddings, letting researchers query 500GB+ of structured and unstructured sustainability disclosures in natural language.
- •Developed chunking and schema-guided LLM pipelines that extract structured ESG fields from unstructured disclosures.
- •Shipped a React dashboard and chat interface for 30+ researchers, cutting 15+ hours per week of manual review.
- •Integrated an LLM layer grounding answers in retrieved disclosures with citations to reduce hallucination, plus a feedback loop capturing researcher ratings to refine retrieval accuracy over time.
Sigma Computing, New York, NY
Software Engineer Intern
- •Delivered four production features end-to-end — owning implementation, testing, and deployment — including a condition-based formula visualization tool, Form v2, headers, and navigation used by 60+ enterprise organizations.
- •Optimized rendering of large data grids with memoization and virtualization, improving dashboard responsiveness.
- •Wrote Cypress end-to-end tests for critical workbook flows, catching regressions before they reached production.
World Salon, Los Angeles, CA
Software Engineer
- •Launched an events platform powering 130+ events for institutions, speakers, attendees, BDR, and internal teams.
- •Engineered scraping and OpenAI-powered profiling pipelines that processed 58,000+ candidate profiles end-to-end, automating the company's core speaker-sourcing operation.
- •Designed REST APIs with JWT auth and role-based access control across production services and admin routes.
- •Refactored a monolithic backend into modular payment and event services, reducing request latency by 20%.
- •Containerized and deployed applications on AWS using Docker, EC2, S3, and GitHub Actions CI/CD pipelines.
USC Marshall School of Business, Los Angeles, CA
Research Assistant
- •Engineered fault-tolerant ETL pipelines chaining Selenium scraping, OCR, and indexing to ingest 15,000+ sustainability reports across 10 years of S&P 1500 filings into a unified research knowledge base.
- •Modeled normalized PostgreSQL schemas with targeted indexing over 2M+ extracted data points, cutting query latency by 12% and powering fast downstream analytics, semantic retrieval, and reporting.
- •Parallelized PDF extraction with multithreading, cutting processing time 30% over the prior sequential pipeline.
Education
University of Southern California
Masters of Science in Computer Science | GPA: 3.81/4.0
Developed advanced technical expertise in algorithms, database systems, and web technologies while enhancing problem-solving skills and innovation.
University of Mumbai, Mumbai, India
Bachelor of Technology in Information Technology | GPA: 3.8/4.0
Gained a solid foundation in operating systems, machine learning, software engineering, and computer networks.
Projects
A selection of projects I've built
miniredis - Redis-Compatible In-Memory Store
A Redis-compatible in-memory store written from scratch in C++17 — non-blocking epoll/kqueue reactor over the RESP protocol, hand-written skip-list sorted sets, AOF persistence, pub/sub, and replication. Reaches 984K+ ops/sec.
TalkToData - Natural Language SQL
AI-powered SQL query interface that converts plain English to SQL. Supports PostgreSQL, MySQL, SQLite, SQL Server, and MongoDB with AI-driven query explanations and error fixing.
RoomReserve - Hotel Booking API
Full-featured hotel booking backend API with user authentication, hotel/room management, booking lifecycle, and mock payment integration — 20+ REST endpoints on a normalized relational schema with concurrency-safe double-booking prevention.
Stock Insight Application (Web)
Full-stack stock trading platform with real-time data from Finnhub and Polygon APIs. Features portfolio management, watchlists, and interactive charts with responsive Angular Material design.
World Salon Website
Built during my internship at World Salon. Event creation platform with JWT authentication, role-based access control, and integrated payment workflows.
Cataract Detection with Explainable AI (XAI)
Led team of 3 to develop CNN-based cataract detection system achieving 97% accuracy with explainable AI integration. Integrated GradCAM for visualizing model decisions.
Fake News Detection
Developed and benchmarked multiple deep learning architectures achieving 93% accuracy. Achieved 94% precision, recall, and F1-score on WELFake and Kaggle datasets with 115K+ articles.
Testimonials
What people say about working with me
“I mentored Rutwik during his internship at Sigma. Rutwik is a diligent and professional engineer who continually impressed us with his ability to move at a blistering pace without sacrificing quality. During his 12 weeks, he independently shipped a highly-requested feature to customers and onboarded...”
Jonathan Zhang
Frontend Engineer
Sigma Computing
Publications
Peer-reviewed research papers I've authored
Exploring the Potentials of Explainable AI for Early Cataract Detection to Foster Accessible Healthcare
XAI meets Ophthalmology: An Explainable Approach to Cataract Detection using VGG-19 and Grad-CAM
Federated Learning to Preserve the Privacy of User Data
Literature Survey on virtual laboratory for secondary students
Get in Touch
I'm always open to new opportunities and interesting conversations