- 🌱 I’m currently learning React, Python, and Data Science
- 💻 I work as a Software Engineer at G4 Educação
- 🛠️ My tech stack covers various languages, frameworks, databases, and tools (see details below!)
- 📫 How to reach me: g.a.santos.dev@gmail.com
- 😄 Fun fact: I love hackathons, and I'm a huge fan of parmegiana!
Details
- Node.js: My go-to for scalable backend applications, APIs, and tooling.
- Python: Used for scripting, automation, data science, and backend development.
- Go: For high-performance, concurrent systems and microservices.
- Java & Kotlin: Experience with JVM-based enterprise and Android projects.
Details
- React & Next.js: For building modern, scalable web applications.
- Vite: Preferred tooling for fast and efficient frontend development.
- TypeScript & JavaScript: Core languages for client-side and server-side code.
Details
- Django REST Framework: For robust and scalable REST APIs in Python.
- Express: Minimal and flexible Node.js web application framework.
- NestJS: TypeScript-first, scalable Node.js backend framework.
- Spring & Quarkus: For enterprise-grade Java applications and microservices.
Details
- React Native: For cross-platform mobile apps using JavaScript/TypeScript.
- Flutter: For high-performance native interfaces on iOS and Android.
Details
- Relational Databases: PostgreSQL, MySQL, MariaDB, SQLite
- NoSQL: MongoDB
- Cache/Message Brokers: Redis, RabbitMQ
- Web Servers: Nginx
Details
- Version Control: Git (daily usage)
- Shell Scripting: Bash
- Containers & Orchestration: Docker, Docker Compose, Kubernetes
- CI/CD: GitHub Actions, Jenkins
Details
- LLMs: Experience running and fine-tuning Large Language Models locally (e.g., Ollama, OpenAI APIs).
- RAG (Retrieval-Augmented Generation): Applied RAG pipelines using FAISS for efficient vector search and context retrieval.
- Frameworks: Hugging Face Transformers, LangChain for prompt management, chaining, and orchestration of LLMs.
- ML/DL Frameworks: PyTorch, TensorFlow, scikit-learn for model building and training.
- Data Tools: Pandas, NumPy, Jupyter for data analysis and experimentation.