I'm a Python backend developer with a Systems Engineering background. I build backend services and the AI layer on top of them: APIs that integrate LLMs, automate manual work and keep a person in control where it matters.
I built SIVIDEM from scratch to production, a public health surveillance system that turns official data into indicators, maps and forecasts, and I write LLM integrations with multiple providers, structured output and tests. Currently building an AI agent with FastAPI and LangGraph.
Backend & Applied AI:
- REST APIs with FastAPI
- LLM integration: multiple providers, structured output, retries and validation
- Background processing with queues (Redis, RQ)
- Docker and Docker Compose
- Testing with pytest
Data:
- ETL pipelines and data quality
- SQL and PostgreSQL
- Data analysis with pandas
- Dashboards with Streamlit and Power BI
- SIVIDEM: epidemiological surveillance system deployed as Docker Compose services, with a queued processing worker, role-based access and a plugin architecture for new diseases.
- Dengue forecasting research: data pipeline, model comparison tracked in MLflow and the ablation study behind SIVIDEM's production model.
- llm_connector: multi-provider LLM integration layer for a multiplayer game, with tool calling, validation and a pytest suite.
- Retail customer analytics: data quality audit, customer segmentation and archetypes for a fashion brand.
"Do. Or do not. There is no try." – Yoda
"Clean code is the way." – Din Djarin
May the code be with you 🖖