AlexandreTeixeira.dev
AI-Augmented Product Engineer
I turn complex ideas into reliable, usable software end to end, from architecture and implementation to automated testing, review, deployment, and ongoing validation.
Brainstorm -> Arch Design -> Build -> Test -> Audit -> Iterate -> Ship
Open Source
42 Porto
A peer-evaluated software engineering curriculum built around learning by doing. The common core moves from C foundations into C++ and Unix systems work across memory ownership, parsing, IPC, concurrency, graphics, algorithms, networking concepts, debugging, code review, and independent problem solving.
Engineering focus & working stack
I use AI as part of the engineering workflow for research, implementation, review, testing, and coordination, but not as a substitute for architecture, judgment, or independent verification.
The recurring goal is the same across stacks: make behavior observable, failures reproducible, changes reviewable, and validation cheap enough to run continuously.
Software architecture
Turning product intent into clear boundaries, maintainable structure, observable behavior, and systems that remain safe to change.
Test automation & validation
Regression suites, validation harnesses, end-to-end checks, failure observability, and independent verification as core engineering tools.
Application security
Defensive engineering, careful trust boundaries, review discipline, and changes that preserve security properties instead of bypassing them.
AI-augmented engineering
Using AI deliberately for research, implementation, review, testing, and coordination while keeping engineering judgment and verification in the loop.
Reproducible delivery
Docker, Linux, Git, CI/CD, deterministic workflows, and environments that make failures repeatable and deployments easier to trust.
Systems foundation
C, C++, Unix, networking, concurrency, IPC, parsers, algorithms, memory management, and low-level debugging from 42 Porto.