AI Quality Engineer · SDET · Test Architecture · Agentic AI
Quality engineering is not about finding bugs. It's about designing the systems, feedback loops, and workflows that prevent them at scale.
I'm a Quality Engineer and SDET with 13 years in technology and 9 years focused on software quality. My work sits at the intersection of test architecture, AI-augmented automation, and engineering excellence.
Currently building at the frontier of Quality Engineering + AI - where automation is intelligent, quality is systemic, and teams move faster because quality is designed in, not bolted on.
Test Automation
Languages
AI & Emerging
CI/CD & Tools
View the live Consolidated Test Dashboard - aggregated, always-up-to-date test results across all 5 repositories below.
Traditional QA
| Project | Stack | Description |
|---|---|---|
| calculator-playwright | Python · Playwright · Pytest | Web calculator with 23 E2E tests and 6 documented bugs |
| saucedemo-playwright | TypeScript · Playwright · POM | 20 E2E tests for e-commerce using Page Object Model |
| restful-booker-restassured | Java · Rest Assured · TestNG | 7 API tests covering full CRUD operations |
AI QA
| Project | Stack | Description |
|---|---|---|
| llm-test-case-generator | Python · OpenAI API | Generates structured test cases from feature descriptions using an LLM |
| llm-as-judge | Python · OpenAI API | Uses an LLM to evaluate the quality of test cases generated by another LLM |
rag-qa-validator |
Python · RAG | Validates whether LLM answers stay faithful to source documentation - coming soon |
ai-qa-agent |
Python · LLM · Agentic AI | Full QA agent with memory, tools, and autonomous flow - coming soon |
Pipeline Orchestration
| Project | Stack | Description |
|---|---|---|
| qa-portfolio-pipeline | GitHub Actions · Python | Orchestrates all 5 repositories' CI in phases and publishes the consolidated dashboard above |
- 🤖 AI Agents and Multi-Agent Systems
- 🔗 MCP (Model Context Protocol)
- 🧪 LLM Testing and non-deterministic validation
- 🎯 Fine-tuning models for QA use cases
- 🔐 Penetration testing for AI systems
- Reduced monthly production bugs from 14 to 0 at AB InBev (Bees Brasil)
- Reduced QA cycle from 7 days to 1 at SoftExpert
- Designed AI-assisted QA workflow with prompt engineering at RDI Software
- Created "Intelligent Coverage Review" - a shift-left QA process using an AI agent with a specialized prompt to surface edge cases, side effects, and root cause analysis before testing begins, cutting ticket analysis time significantly
- Led E2E automation architecture across multiple distributed products
