Back-End Developer focused on C# / .NET, with solid experience in data (SQL Server and PostgreSQL) and applied AI when products need grounded context and reliable answers.
I've been in tech since my twenties. Today I design APIs, integrations, and data-driven services—from relational modeling to LLMs with RAG, evaluation, and local inference where it makes sense.
- 🔭 ASP.NET Core, integrations, and persistence on SQL Server and PostgreSQL
- 🌱 Software architecture, DevOps, and AI engineering (RAG, evaluation harnesses, training for local models)
- 🌐 JavaScript and Angular when the solution includes a UI (e.g. CDB Calculator)
- 💼 Open to Back-End Developer roles and projects that combine data + AI
| Project | Summary |
|---|---|
| cdb-investment-calculator | .NET 10 API (Domain/Application layers), xUnit tests, CDB yield calculation, and an Angular client |
| fintech-aurea-bank | Digital account dashboard (FIAP) built with HTML, CSS, and Tailwind |
I work at the intersection of product software and model-powered systems:
- RAG — context retrieval (vector stores + documents), prompt assembly, and answers grounded in what the organization actually knows.
- Evaluation harnesses — test suites, metrics, and regression to compare prompt, model, or pipeline versions before production.
- Local AI — experimentation with fine-tuning/training and on-prem or controlled-environment inference, reducing reliance on external APIs alone.
Typical stack in this space: Python for orchestration and experiments; .NET services when the business core already lives on the Microsoft stack.
Languages & runtimes
Databases
AI, DevOps & tools
Kubernetes and Terraform — learning and hands-on in lab environments.
