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JhoanGZ/README.md

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🌍 About Me

Backend-focused Full-Stack Engineer building scalable SaaS platforms and modular AI-oriented backend systems.

My work centers around designing reliable systems with clear boundaries, explicit contracts, and long-term maintainability.

I focus on:

  • Multi-tenant SaaS architecture
  • Domain-driven backend design
  • Permission-based access control (RBAC / PBAC)
  • Retrieval-Augmented Generation (RAG) workflows
  • Containerized and reproducible environments
  • Secure-by-default API design

🚧 Currently Building

  • AI-augmented backend workflows
  • Modular RAG infrastructure
  • Delivery-focused backend systems with strong architectural boundaries
  • Refining system design, observability, and production readiness
  • Portfolio update
  • New keyboard optimization for workflow

βš™οΈ Engineering Principles

  • Explicit boundaries over implicit coupling
  • Backend-enforced business rules
  • Secure-by-default design
  • Reproducible environments
  • Long-term maintainability over short-term hacks
  • Clarity of contracts between services

🧠 Engineering Identity

const jhoanGutierrez = {
  role: "Backend Engineer | AI-Oriented Systems | Full-Stack Developer",

  focus: {
    saas: "Multi-tenant institutional platforms",
    ai: "Semantic retrieval engines & RAG-based workflows"
  },

  stack: {
    languages: ["Python","Ruby","TypeScript","JavaScript","SQL","Java","MongoDB","C"],

    backend: {
      primary: ["Ruby on Rails","FastAPI"],
      secondary: ["Node.js (Express)","Flask","Spring Boot","Express"]
    },

    frontend: ["React","Next.js"],

    databases: {
      relational: ["PostgreSQL","MySQL"],
      vector: ["pgvector"],
      noRelational: ["mongoDB"]
    },

    infrastructure: [
      "Docker","Docker Compose","Redis","Sidekiq","Nginx","AWS (EC2, S3)"
    ],

    tooling: [
      "Git", "GitHub Actions", "Swagger/OpenAPI","CURL", "Postman", "Jira", "nvim"
    ],

    security: ["JWT (HttpOnly Cookies)","RBAC / PBAC"]
  },

  architecture: [
    "Clean Architecture", "SOLID", "Domain Modeling", "Service Layer Pattern", "Multi-Tenant Isolation",
    "LLM Adapter Pattern"
  ],

  flagshipProjects: [
    "Toolsticket – Multi-tenant SaaS module",
    "VectorEngine – Modular RAG backend infrastructure"
  ],

  currentFocus:
    "Building production-ready backend systems with strong boundaries, scalable data models, and AI-augmented workflows.",

  mindset:
    "Ship clean systems. Improve continuously. Optimize intentionally.",

  funFact:
    "I don't always debug… but when I do, it's in production."
};

πŸ€– VectorEngine - Modular AI-Oriented Backend Infrastructure

A containerized semantic retrieval backend designed to power context-aware AI applications.

Built to support structured retrieval workflows rather than simple chatbot interactions.

Architectural Principles

  • Clean separation between domain, orchestration, and infrastructure layers
  • Adapter pattern for LLM provider abstraction
  • Deterministic fallback logic for resilience
  • Replaceable vector store implementation (pgvector)
  • Structured JSON response contracts

Stack

  • FastAPI
  • PostgreSQL + pgvector
  • sentence-transformers (local embeddings)
  • OpenAI-compatible LLM API integration
  • Docker Compose environment

VectorEngine is designed as a reusable semantic infrastructure layer focused on maintainability, replaceability, and backend clarity.


🏫 Toolsticket - Multi-Tenant Educational Incident Management Module

A domain-driven SaaS module designed for institutional incident management in educational environments.

Toolsticket models real institutional hierarchies, strict tenant isolation, and permission-based access control.

Key Engineering Aspects

  • Multi-tenant data isolation
  • Institution-scoped RBAC
  • Dynamic UI rendering based on permission policies
  • Category-based supervisory filtering
  • Strict backend-enforced domain rules
  • Performance optimization through query tuning and caching strategies

Stack

  • Next.js + React Query
  • Ruby on Rails API (JWT authentication, scoped queries)
  • MySQL relational modeling
  • Redis + Sidekiq for background processing
  • Dockerized development environment
  • GitHub Actions for CI validation

This project demonstrates non-trivial domain modeling, secure multi-tenant architecture, and backend reliability in production-oriented systems.


πŸ›  Core Technologies

Tech Stack

Python
Python
JavaScript
JavaScript
TypeScript
TypeScript
React
React
Docker
Docker
Java
Java
AWS
AWS
Nginx
Nginx
MySQL
MySQL
REST API
REST API
GitHub
GitHub
csharp
C#
Ruby
Ruby
Rails
Rails
FastAPI
FastAPI
Next.js
Next.js
PostgreSQL
PostgreSQL
Redis
Redis
MongoDB
MongoDB
Git
Git
GitHub Actions
CI/CD
Linux
Linux
Postman
Postman
C
C
Neovim
Neovim

🀝 Connect With Me

Portfolio LinkedIn


"Build systems that scale. Design boundaries that last. Engineer with intent."

Pinned Loading

  1. VectorEngine VectorEngine Public

    Containerized semantic retrieval engine built with FastAPI, PostgreSQL (pgvector), and clean architecture principles.

    Python 1

  2. Code_Snippet_Library Code_Snippet_Library Public

    JavaScript 1

  3. quiz-app quiz-app Public

    Quiz application built with Rails 8, Devise, Pundit, Hotwire, Tailwind CSS, and PostgreSQL.

    HTML 1

  4. Harvard_CS50 Harvard_CS50 Public

    Harvard's CS50 Coursework and Projects

    C 1

  5. Grade_Manager Grade_Manager Public

    Java

  6. fmk-task-api fmk-task-api Public

    Technical Test | Task management REST API built with NestJS, PostgreSQL and TypeORM.

    TypeScript