Brazil / backend product systems / PT-BR native / English-first portfolio
Work
Four are public repositories with runnable engineering proof. Two stay private, but the cases still show architecture, constraints, operating flows, and why the system was shaped the way it was.
An agent-trust platform with simulation, policy evaluation, approvals, execution receipts, and rollback visibility.
The core signal is not just AI orchestration. It is the trust layer around execution: propose, simulate, evaluate, approve, execute, receipt, and rollback visibility.
A multi-tenant onboarding SaaS with billing, follow-up automation, storage controls, and product-like operational docs.
This project shows that I can work beyond CRUD: tenant isolation, budgeted AI usage, billing webhooks, storage policy, and cron-driven follow-ups.
A lightweight signup risk API with OpenAPI contract, key management workflow, rate limits, and deploy verification scripts.
MailSieve is a good example of a small API product where contract clarity, ops scripts, and monetization readiness matter more than feature count.
An educational neural network implementation with deterministic evaluation, logs, tests, and a reproducible pipeline.
This stays public because it shows engineering discipline inside a study project: reproducible evaluation, smoke checks, and structured docs.
A private case study for quote generation and WhatsApp-based sharing, built as a mobile-first SaaS workflow on Next.js and Supabase.
The strongest signal here is product workflow design: quotes, public share links, mobile-first UX, and AI-assisted copy in a small but real business flow.
A private case study for collaborative accessibility audits, QR-linked public certificates, and evidence-driven scoring.
This is the private project with the clearest public-interest angle: weighted checklists, evidence capture, moderation, and a public certificate layer.