"Technology allows us to change the world, science allows us to improve it."

I am a Senior Backend Engineer based in Brazil, fascinated by the intersection of complex software systems and scientific principles.

Currently, I help scale distributed systems at Sunne, one of the fastest-growing startups in the renewable energy sector. Outside of my main role, I'm deeply invested in building independent products (Micro-SaaS) and open-source libraries that bridge the gap between theoretical science and practical software engineering.

My focus is on building resilient architectures with zero friction and high mathematical precision.

I leverage a powerful set of tools to build scalable applications and data-driven solutions.

• Core: Node.js, TypeScript, Python (for Data Science and Machine Learning).
• Architecture: AWS, GCP, Microsservices, Event-Driven Design, PostgreSQL, Redis.
• Science & Data: Statistical Analysis, Machine Learning basics, Physics simulations.

A Zero-Dependency Time-Weighted Retrieval (TWR) Suite for Node.js, AI Agents, and RAG Systems.

Temporal RAG is a pure mathematical middleware that adds human-like forgetting and memory consolidation to your AI Agents. It acts as a Time-Weighted Re-Ranker, fusing the spatial results from your Vector Database (e.g., Qdrant, Pinecone, Chroma) with temporal decay algorithms derived from cognitive science.

The AWS Cost & Security Scanner. I built InfraLens to solve a recurring problem I saw in the market: wasted cloud resources.

• What it is: An agentless scanner that connects securely to AWS to find idle resources (like unused NAT Gateways or zombie RDS instances) and security risks.
• Stack: Vue 3, Node.js, AWS SDK.

A Physics-Inspired Event Framework. Born from a desire to make event-driven architectures cleaner. It treats business objects as "Particles" and events as "Bosons," allowing for highly decoupled logic in TypeScript applications.

• Status: Open Source (Experimental).

Scientific Computing for Node.js. A library bringing essential statistical functions and probability distributions (Pearson, Binomial, Poisson) to the JavaScript ecosystem with a focus on performance and accuracy.

I treat software development as an evolving craft. I believe that:

1. Simplicity is Key: The best code is the one that doesn't need to be written. Complex problems don't always need complex solutions.
2. Systems over Scripts: I design architectures meant to evolve and survive scaling, rather than quick fixes.
3. Data-Driven Decisions: Intuition is good, but statistical significance is better.