Fullstack Developer
Hey! I am João Alves, a Fullstack Developer with 4 years of experience, specialized in TypeScript (Next.js) and Python in fullstack development. I build complete solutions from backend to frontend, without being limited to any specific language or stack, focusing on performance, security, and efficient design.
Based on Brasília - Brazil

That's my story

I have been working as a Fullstack Developer for 4 years, building complete solutions from backend to frontend, focusing on performance, security, and efficient design.

2018 - 2020

I enrolled in the Software Engineering program at the University of Brasília. During this period, I primarily developed applications for academic use. One notable project was integrating the “Guardiões da Saúde” app—which tracked potential COVID-19 exposures in real time—with a Telegram chatbot, enabling users to report their symptoms without installing an external app.

DoctorS

A chatbot developed in Flask that integrated with the Guardiões da Saúde app to track Covid-19 symptoms in real-time, using Firebase as a database and the Telegram API for communication.

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2020 Certifications

In 2020, I earned several important certifications:

✅ Certified Network Security Specialist (CNSS) – International Cybersecurity Institute (ICSI)
✅ Cybersecurity Essentials – Cisco Networking Academy
✅ Bootcamp in CyberSecurity Analysis – XP Educação (IGTI)

10/2020 - 2021: Internship at DBS Web

I began an internship at DBS Web as a fullstack web developer. During this time, I developed and deployed a time tracking application for employees and was responsible for the security and backend of various client projects.

Hit The Dot

An electronic time tracking system developed with Flask, using Firebase for authentication, MySQL for data storage, and Redis for performance optimization and real-time shift tracking.

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July 2023: Course Transfer & Freelancing

In July 2023, I transferred from the Software Engineering program at the University of Brasília to the Computer Science program at the Universidade Católica de Brasília. Around the same time, I began working as a fullstack freelance developer.

2023 → 2024: LMS for Instituto Panapaná

I developed a course management system (LMS) for Instituto Panapaná, a platform dedicated to providing free education for young people in vulnerable situations, prioritizing accessible learning opportunities over traditional administrative enhancements.

Instituto Panapaná

A LMS designed for Instituto Panapaná, focused on delivering free educational resources to young individuals in vulnerable circumstances, emphasizing accessible learning rather than conventional academic administration.

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2024 - Present: Developing AILib

I am currently developing AILib, a system built with Electron.js and React that leverages AI APIs to enhance the reading and annotation of books. Key features include ultra-detailed book summaries, advanced Retrieval-Augmented Generation (RAG) with QDrant as the vector database, and parallelized document processing—capable of embedding up to 500 pages per minute into a SQLite database, that handles the Parent Document Retrieval with QDrant.

AILib

A system built with Electron.js and React that leverages AI APIs to enhance the reading and annotation of books. Key features include ultra-detailed book summaries, advanced Retrieval-Augmented Generation (RAG) with QDrant as the vector database, and parallelized document processing—capable of embedding up to 500 pages per minute into a SQLite database, that handles the Parent Document Retrieval with QDrant.

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10/2024 - 03/2025: Kairos

I've worked on developing a digital content generation system for clients. This application generates text using large language models (LLMs), automatically curates relevant news for each client, and produces AI-generated audio and video content. The system is built with Next.js on the frontend, FastAPI on the backend, employs REDIS for real-time polling via callbacks, uses MySQL for data storage, and leverages QDrant as a vector database.

Kairos

A web application for creating automated content using large language models (LLMs). The app curates news, generates text, and produces AI-generated audio and video content. Developed with Next.js, FastAPI, MySQL, and Redis, the system leverages QDrant as a vector database for efficient data indexing.

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2025: Developing RAG.NET

Building RAG.NET has been an exciting challenge. From designing a flexible workflow structure to implementing advanced AI-driven processing techniques, every step has required balancing performance and modularity. The system empowers users to tailor their RAG pipelines with cutting-edge chunking, querying, and ranking methods. As development progresses, I’m expanding integrations with new embedding and conversation providers, pushing the boundaries of what’s possible in intelligent retrieval systems.

RAG.NET

A modular system built with ASP.NET Core, Angular 19, PostgreSQL, and QDrant, designed to create and execute powerful RAG workflows with customizable AI components.

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Skills

I have a diverse skill set that spans backend, frontend, databases, and other complementary technologies. Explore my proficiencies in various technologies and tools that power my projects.

Backend

This section showcases my backend development expertise, focusing on building robust, scalable, and secure systems. It highlights my proficiency in programming languages, frameworks, and technologies that power server-side logic and data management.

Frontend

This section demonstrates my expertise in crafting engaging and responsive user interfaces. I combine modern frameworks and design principles to deliver seamless, interactive, and visually appealing front-end experiences.

Databases

My experience with databases spans from traditional relational systems to modern NoSQL and vector-based solutions. I design and optimize database schemas, ensuring data integrity, performance, and scalability across various projects.

Others

Beyond core development, I excel in integrating complementary technologies and tools that enhance security, deployment, and collaboration across projects.

SEARCH ON MY PROJECTS

Python

    Logo of RAG.NET

    RAG.NET

    Under Development

    A modular system built with ASP.NET Core, Angular 19, PostgreSQL, and QDrant that enables the creation of custom Retrieval-Augmented Generation (RAG) workflows. Users can configure Chunkers, Query Enhancers, Filters, and Rankers, integrating technologies like Proposition Chunking, Auto Querying, Self Querying Retrieval, and CoHere Reranker.

    Logo of Kairos

    AILib

    Under Development

    A system built with Electron.js and React that leverages AI APIs to enhance the reading and annotation of books. Key features include ultra-detailed book summaries, advanced Retrieval-Augmented Generation (RAG) with QDrant as the vector database, and parallelized document processing—capable of embedding up to 500 pages per minute into a SQLite database, that handles the Parent Document Retrieval with QDrant.

    Logo of Kairos

    Kairos

    A web application for creating automated content using large language models (LLMs). The app curates news, generates text, and produces AI-generated audio and video content. Developed with Next.js, FastAPI, MySQL, and Redis, the system leverages QDrant as a vector database for efficient data indexing.

    Logo of IP Tracker

    IP Tracker

    An IP tracking application that allows users to search for geolocation information of IP addresses. Developed with Angular, the application utilizes a mapping library to display the location and makes requests to geolocation APIs to obtain accurate data.

    Logo of Kanban

    Kanban

    A Kanban-style task management system built with Next.js and MongoDB, using React Query for efficient state synchronization between client and server.

    Logo of DevLinks

    DevLinks

    An application built with Next.js, Tailwind CSS, and MongoDB to store and share developers' social media links, with authentication and profile visibility options.

    Logo of Maryna Carvalho Advocacia

    Maryna Carvalho Advocacia

    Landing page for a law firm, developed with Next.js and TailwindCSS. The site includes a contact form integrated with ReSend for email sending.

    Logo of Corpo e Mente Clinical Space

    Corpo e Mente Clinical Space

    Website for a psychology clinic, featuring an appointment booking system and authentication with multiple permission levels. Developed with Next.js, TailwindCSS (ShadCN), and MongoDB.

    Logo of Hit the Dot

    Hit the Dot

    An electronic time tracking system developed with Flask, using Firebase for authentication, MySQL for data storage, and Redis for performance optimization and real-time shift tracking.

    Logo of DoctorS

    DoctorS

    A chatbot developed in Flask that integrated with the Guardiões da Saúde app to track Covid-19 symptoms in real-time, using Firebase as a database and the Telegram API for communication.