Rafael Pupio Vieira · AI Engineer

Rafael
Pupio
Vieira

Work authorization — no visa needed: US Brazil EU·27 + EEA Switzerland

US · Italian · Brazilian citizen — plus simplified Mercosur residency rights across South America

AI Engineer building agents & automation on 10+ years in administration, operations & financial operations

0+
Yrs admin · ops · financial ops
0
AI certifications
0
Citizenships
0
Trading agent — retrains daily
Builds Daily

The Builds

FOLIO 01

Live cargo — what I'm building, how the AI is actually applied, and what it runs on.

001

Daily-Learning Trading Agent

In Build

An end-to-end AI day-trading R&D pipeline. The core is a deep-learning agent architected to retrain on every trading session — each day's market data feeds the next day's model, so the system compounds instead of going stale. Claude Code operates as an active engineering partner across architecture, code, and research.

AI appliedDeep-learning agent design · daily retraining loop · agentic engineering with Claude Code driving architecture & implementation
Domain edgeMarket structure & risk framed by 10+ years of FP&A discipline — the model's objectives are set by someone who has owned a P&L forecast
StatusActive R&D — architecture documented, agent in iterative build
Deep LearningAgent ArchitectureRetraining PipelineClaude CodeAgentic EngineeringQuant Research
002

Persistent Context System

Shipped

The knowledge layer that makes the trading agent buildable: TRADING-KNOWLEDGE.md and DAILY-LEARNING-AGENT.md — foundational documentation engineered as durable LLM context. Dropped into the project repo, they brief every fresh Claude session on the domain, the architecture, and the decisions already made. No re-explaining, no drift.

AI appliedContext engineering · documentation-as-memory · repo-native knowledge base that turns a stateless model into a briefed teammate
Why it mattersAgentic projects live or die on context quality — this is the difference between an assistant and a collaborator
StatusShipped — in daily use powering build 001
Context EngineeringLLM MemoryKnowledge Base DesignPrompt EngineeringDocs-as-Code
003

This Site

Live

You're looking at build 003. Hand-rolled HTML, CSS and JavaScript — zero frameworks, zero templates — shipped through an agentic workflow: three competing design concepts prototyped live, headless-browser visual QA on every iteration, then this MANIFEST × LEDGER blend chosen and cut in a single working session.

AI appliedAgentic build loop — spec → concept prototypes → automated screenshot verification → ship · Claude as design & engineering partner
Under the hoodVanilla JS · IntersectionObserver reveals · CSS-only marquees · reduced-motion support · no dependencies
StatusLive — and iterating
Agentic WorkflowRapid PrototypingAutomated Visual QAVanilla JSMotion Design

Shipping Log

FOLIO 02

Public repositories, pulled straight off the docks at github.com/RafaelPupio and gitlab.com/RafaelPupio. Repo descriptions stay in English.

Last sync: 2026-09-01 · Auto-refreshes daily
★ 1

ChurchChatBox

TypeScript · ★ 1 · GitHub

Secretaria Virtual — a WhatsApp church secretary bot (pt-BR). Automates the secretarial front desk over the channel Brazilian communities actually use. Next.js · PostgreSQL · Drizzle ORM.

WhatsApp BotNext.jsPostgreSQLDrizzlept-BR
Inspect →
Live

landing-page-cav

TypeScript · GitHub

Landing page for Comunidade Árvore da Vida (Lucas do Rio Verde, MT). Next.js 16 · React 19 · TypeScript, with all content in a single Zod-validated JSON config, a dev-only content editor, SEO and full accessibility. Tested and deploy-ready.

Next.js 16React 19ZodSEOA11y
Inspect →
On Watch

service-watchdog

Python 100% · GitHub

Single-file, cross-platform service monitoring. Checks what you tell it to check, repairs only what is actually down, and reports outward — a dead-man's switch means a dead machine still raises an alarm.

DevOpsSREMonitoringSelf-Healing
Inspect →
Shipped

purged-walkforward

Python 100% · GitHub

Purged, embargoed walk-forward cross-validation for time series with overlapping labels. Shuffled K-fold lies on temporal data — look-ahead bias and label-overlap leakage inflate scores. This is the NumPy-only, scikit-learn-compatible fix: walk-forward ordering, purging, embargo periods, uniqueness weighting. Honest validation for models that trade.

Machine LearningTime SeriesCross-Validationscikit-learnNumPy
Inspect →
Tested

MORDOMO

TypeScript · GitHub

AI church secretary. A streaming chat interface driven by a single tool-using agent — knowledge search, calendar, prayer requests, human escalation — with RAG over pgvector and source citations. Document ingest runs as a multi-stage pipeline with extractor and verifier agents; back-office work (weekly AI reporting) goes multi-agent. Next.js · Postgres · Vercel AI SDK. Fully tested.

AI AgentsRAGpgvectorTool UseMulti-Agent Pipelines
Inspect →
Opening

GitLab · @RafaelPupio

New berth · GitLab

Manifest just opened at this port. Projects will appear in the log as they ship — this page re-checks the docks every day.

GitLabIncoming
Inspect →

Method & Stack

FOLIO 03

The tools, layer by layer — every line backed by a public repo you can open.

AI / MLDeep-learning agent with a daily retraining loop (trading pipeline) · RAG over PostgreSQL + pgvector embeddings with source citations · multi-stage document ingest with extractor → verifier agent chains · tool-using agents on the Vercel AI SDK (knowledge search, calendar, human escalation) → MORDOMO, trading agent
ML RigorPurged & embargoed walk-forward cross-validation for overlapping-label time series — look-ahead bias and label-leakage control, uniqueness weighting; NumPy-only, scikit-learn-compatible API → purged-walkforward
LanguagesPython for ML and systems tooling · TypeScript end-to-end for product code
Backend / DataPostgreSQL (+ pgvector) · Drizzle ORM · Next.js server routes · Zod-validated typed configs → MORDOMO, ChurchChatBox, landing-page-cav
FrontendNext.js 16 · React 19 · SEO & WCAG accessibility · dependency-free motion design in vanilla JS/CSS → landing-page-cav, this site
Agentic Eng.Claude Code as engineering partner — spec → persistent .md context files → plan-first build → headless-browser visual QA on every iteration → every repo above
Ops / SRECross-platform service monitoring with self-healing restarts and a dead-man's switch — a dead machine still raises an alarm → service-watchdog
rafael@pipeline: ~ $ cat METHOD.md
01 SPEC     — define the mission like an operator: scope, constraints, definition of done
02 CONTEXT  — engineer persistent .md knowledge files so every session starts fully briefed
03 BUILD    — pair with Claude Code: plan first, generate, review every change
04 VERIFY   — tests, screenshots, metrics — ship only what survives inspection
▸ edge: 10+ years inside administration, operations & financial operations.
▸ I don't build AI for demos — I build it for domains I've actually run.
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Credentials

FOLIO 04

Full record on LinkedIn — /in/rafaelpupiovieira.

4.1
AI Fundamentals in Financial Services

University of Oxford — Saïd Business School. AI capability grounded in the domain where I already operate.

Verified
4.2
Claude 101 & Claude Code 101

Anthropic. Certified on the tooling this entire site — and the trading pipeline — is built with.

Verified
4.3
Full-Stack Development

Coursework completed as deliberate technical upskilling — the substrate under the AI layer.

Logged
4.4
A Decade of Operations

10+ years across FP&A, international logistics and business administration. Not a credential — a targeting system. It's how I know which problems are worth automating.

Field-Tested