Backend Engineer transitioning into AI Engineering, based in Brazil.
Currently pursuing a degree in Software Engineering and a postgraduate degree in Artificial Intelligence at PUC Minas, with a background in Finance and professional experience in the field.
4+ years of experience developing APIs, microservices, and production systems in fintech.
| Product | Stack | Description |
|---|---|---|
| Pompter | Next.js, Supabase, Stripe Connect, Vercel | AI prompt marketplace with dynamic variables, creator payouts, and i18n |
| + other projects | Python, React, TypeScript, Node.js, AI/ML | Production fintech systems, APIs, and integrations (private repos & enterprise accounts) |
Each project is built with a production mindset. Not tutorials, not toy demos. These are systems designed to be deployed, evaluated, and maintained.
| Project | What It Does | Core Skills |
|---|---|---|
| docquery | Production RAG system for technical documentation with hybrid retrieval, RAGAS evaluation metrics, and a FastAPI serving layer | RAG · Embeddings · Evaluation · FastAPI |
| agentflow 🚧 | Multi-step AI agent using MCP protocol with tool orchestration, state management, and failure recovery | AI Agents · MCP · LangGraph · Observability |
| llmguard 🚧 | Evaluation and observability framework for LLM systems: golden test sets, LLM-as-judge, cost tracking, and monitoring dashboards | LLMOps · DeepEval · Grafana · OpenTelemetry |
| fraudsense 🚧 | Anomaly detection API combining classical ML scoring with LLM-powered natural language explanations | ML + LLM Integration · XGBoost · FastAPI |
| deployer | Production-ready deployment template for LLM applications: containerization, CI/CD, health checks, rate limiting, structured logging | DevOps · Docker · GitHub Actions · MLOps |