Jorge Zavala.
I build scalable backend systems and custom AI solutions.

I'm a backend developer from Montana, USA specializing in databases, APIs, and AI integration. I've worked with over 100 clients to design robust architectures that power modern applications.
01.About Me
Hello! I'm Jorge, a backend developer who enjoys creating efficient, scalable systems. My journey in software development has been driven by a passion for solving complex problems through clean, maintainable code.
I specialize in building robust APIs, optimizing database performance, and integrating AI capabilities into production applications. Having worked with over 100 clients, I've learned to deliver solutions that not only work but scale with business growth.
Here are some technologies I've been working with:
- ▹ Python / FastAPI
- ▹ Node.js / Express
- ▹ PostgreSQL / MongoDB
- ▹ Google Gemini
- ▹ OpenAI / Stable Diffusion
- ▹ Docker / AWS
02.Things I've Built
Image Prompt Optimizer
An AI-powered image generation tool that solves the common problem of prompt iteration—users typically adjust prompts 5+ times before getting their desired result. Uses GPT-4o-mini to analyze and optimize prompts upfront with intelligent recommendations. Users select or customize descriptions, which are formatted as JSON and sent to GPT Image for precise, high-quality results on the first try.
- Python
- Streamlit
- OpenAI API
- GPT-4o-mini
- GPT Image
- SQLite
- Hugging Face Spaces
High-Performance API Gateway
Designed and implemented a RESTful API gateway handling 10k+ requests per minute for multiple clients. Built with FastAPI featuring JWT authentication, rate limiting, caching strategies, and comprehensive error handling. Optimized response times to under 100ms for 95% of requests through strategic database indexing and query optimization.
- Python
- FastAPI
- PostgreSQL
- Docker
- JWT
- AWS
Database Optimization System
Optimized database schema and queries for a system managing 50M+ records across multiple client projects. Implemented indexing strategies, query optimization, and connection pooling that reduced average query time by 70%. Designed efficient data models with proper normalization and denormalization strategies based on access patterns.
- PostgreSQL
- MongoDB
- Node.js
- SQL
- Performance Tuning