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Work experience

Senior Software Engineer

Intellectsoft • Aug 2025 - Present (contractor)

• Designed and implemented a new API to enable quick comparison of different GenAI models
• Investigated and resolved critical issues in the backend systems of multiple existing applications, enabling deployment of 5 previously blocked apps to production
• Currently developing RAG capabilities for a QnA agent, including building an ETL pipeline, integrating a vector DB and implementing the retrieval logic

Senior Software Engineer

Waivern • Feb 2025 - Present (freelance)

• Led initial development of an open-source framework for GDPR/AI Act compliance analysis
• Designed a modular plugin system to support extensibility across diverse legal and technical use cases
• Currently advising as a technical consultant: reviewing system design, contributing selectively, and helping with the long-term engineering direction

Senior Software Engineer

Sourcery AI • Nov 2021 - Feb 2025

• Developed LLM-powered AI agents for automated code reviews and bug fixing
• Re-architected an event-driven GitHub/GitLab bot infrastructure supporting natural language comment commands
• Owned and implemented features like automated PR titles and summaries, Mermaid diagram visualization, and security-focused reviews — all widely adopted and loved by users
• Built evaluation datasets and scripts for AI-generated patches, using LangSmith for testing and observability
• Improved our CLI, GitHub Action, and IDE extensions to streamline workflows and increase adoption
• Led codebase modernization efforts; replaced Isort, Black and PyLint with Ruff; upgraded Python/runtime dependencies for a smoother dev experience
• Enhanced our internal static analysis and refactoring engine; added linting and refactoring rules

Tech Lead

Elint Tech • Dec 2020 - Nov 2021

• Led a team of 4 engineers in developing a proof-of-concept for automated PDF data extraction, successfully delivering a solution that was adopted by the client
• Architected and implemented a custom OCR solution that outperformed popular commercial tools, including Google Vision, by combining Tesseract with modern open-source, state-of-the-art models
• Designed and implemented serverless document processing pipelines using infrastructure-as-code on AWS

Skills

• Programming Languages: Python (primary, extensive experience), Rust (actively learning, contributed a PR to the Rust compiler), C/C++ (familiar), Shell scripting
• Operating Systems: Linux (Ubuntu, 8+ years personal/professional), Windows (familiar)
• AI & Data: Agentic AI, RAG, MCP; Pydantic, PydanticAI, LangChain, LangSmith, LangGraph; LLM integration, prompt/context engineering, model evaluation; TensorFlow, PyTorch, OpenCV; NumPy, Pandas, Polars
• Backend & DevOps: UV, Pipenv; Click, Typer, MkDocs, Sphinx; SQLAlchemy, Alembic; CI/CD, Git, GitHub, GitHub Actions, Pre-commit; FastAPI, Docker, GCP, AWS
• Code Quality & Testing: Ruff, MyPy, Tree-sitter; Pytest, CodeCov, TDD; focus on type safety, maintainability, robust test coverage, and comprehensive documentation
• Architecture & Strategy: Systems architecture, domain-driven design, modularization, API/service design, event-driven systems, product vision, prototyping & MVP development, user-centric design, metrics-driven decisions, emerging tech adoption, stakeholder collaboration
• Communication & Collaboration: Clear verbal & written communication, async/sync collaboration, active listening, excellent mentor-level code reviews, user & dev documentation, meeting facilitation, cross-functional teamwork
• Mindset: Critical thinking, adaptability, proactivity, continuous learning, positive attitude
• Open Source Projects: Contributed to the Rust compiler. Created Brag AI (still v0.X!), a CLI tool that turns Git commits into polished achievements using LLMs. Open-sourced Master's deep learning research in Boiling Learning.
• Languages: English (professional), Portuguese (native)

Education

Master's in Mechanical Engineering

Universidade Federal de Santa Catarina • 2019 - 2023

• Built and trained AutoML-optimized Convolutional Neural Networks (CNNs) for pool boiling heat flux estimation on 200,000+ images
• Reduced prediction error by 73–80% with models up to 96% smaller than the previous state-of-the-art
• Published in Elsevier's Applied Thermal Engineering: Paper | Thesis

Bachelor's in Mechanical Engineering

Universidade Federal de Santa Catarina • 2014 - 2018

• Worked as a junior researcher for 2.5 years, developing numerical simulators in C++ for computational fluid dynamics