Hi, I'm
Automated test suites wired into the pipeline, BDD, API and performance testing, quality gates in CI/CD.
5+
years of experience
3
companies
Experience at: CODATA · ENACOM · FAPESQ
Automated test suites wired into the pipeline · BDD, API and performance testing
I came into software engineering through quality and automation, which gave me a complete reading of how a system is built, where it breaks and what it takes to keep it running in production.
Today I build web applications, integrate AI solutions and automate processes. These are three layers of the same work: building the system, embedding intelligence in it and automating the operation around it.
My background is in Computational Mathematics, with a degree in Data Science and a master’s in Information Technology researching AI applied to Software Engineering.
Automated tests generated with AI (Claude Code and Codex), running in a CI/CD pipeline with Allure report publishing, removing repetitive manual validation on every release.
Manual test scripts and execution reports for scenarios automation doesn't yet cover, keeping traceability of what was validated before each release.
Understanding the actual process before proposing a solution, including what exists and what cannot break.
Defining boundaries, contracts between components and the data model before the first line of code.
Incremental implementation, with verifiable deliveries instead of a single milestone at the end.
Automated suites wired into the pipeline, static analysis and gates that keep regressions out of production.
Automated releases, tracking behaviour in production and continuous adjustment.
Research
Sep/2025 – present
Educational initiative for training and qualification in generative Artificial Intelligence tools, aimed at promoting positive social impact. Research funded by the state government.
Official source ↗Education
Feb/2025 – present
Systems Management and Development track. Research on AI applied to Software Engineering: machine learning in testing, quality and automation. Study of LLMs.
Feb/2021 – Dec/2022
Supervised and unsupervised ML: classification, regression, decision trees, neural networks. Model evaluation with scikit-learn. MLOps. Big data with PySpark, PostgreSQL and MongoDB.
Jul/2016 – Dec/2021
Mathematical foundation of the models: computational linear algebra, numerical calculus, optimization, numerical analysis and mathematical modeling. Teaching assistant for Calculus II and Discrete Mathematics.
Researcher — IT Analyst | Keep Chat Project
Sep/2025 – present
IT Analyst — Development and Quality
Nov/2024 – present
Software Quality Analyst V — Technical Lead
Feb/2023 – Oct/2024
Software Quality Analyst III
Oct/2022 – Feb/2023
Software Quality Analyst I / Internship
Jul/2021 – Oct/2022
Mobile Developer
Apr/2019 – Jan/2020
Available for consulting, projects and technical conversations.