Software Engineer and Computer Engineering graduate focused on backend and full-stack development. I work with Python, TypeScript/JavaScript, React, Next.js, Node.js, Java/Spring Boot and PostgreSQL.
I have international software development experience from Barcelona, where I worked on production web projects. I’m currently focusing on Python backend development, APIs, data-driven applications and AI/semantic search systems.
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An internship management platform developed as a graduation project in a two-person team.
I built Angular application components and services and integrated REST APIs for student and instructor workflows. The system included separate token-based authentication flows for students and instructors, along with document submission, approval and internship tracking functionality.
Tech: Angular, REST APIs, Token-Based Authentication
GitHub: https://www.twine.net/signin
A full-stack auction platform developed as a graduation project in a four-person team, with two frontend and two backend developers.
I led most of the frontend implementation using Next.js and React and integrated the frontend with backend APIs for product listings, bidding, auction management and shopping cart functionality.
Tech: Next.js, React, REST APIs
GitHub: https://www.twine.net/signin
A backend-first music metadata processing and matching platform currently in development. Built with Python, FastAPI, PostgreSQL and SQLAlchemy.
The system focuses on ingesting, normalizing, matching and searching music metadata, including typo-tolerant and version-aware matching. I’m also building API endpoints, database persistence, migrations and automated tests as the project evolves.
Tech: Python, FastAPI, PostgreSQL, SQLAlchemy, Alembic, Docker, Pytest
GitHub: https://www.twine.net/signin
A lightweight semantic search system that retrieves relevant text chunks based on meaning rather than simple keyword matching.
I built the retrieval pipeline using Python, PostgreSQL/pgvector and Sentence Transformers, generating embeddings and using vector similarity to find the most relevant content for a query. The project helped me explore practical semantic retrieval and the foundations used in RAG systems.
Tech: Python, PostgreSQL, pgvector, Sentence Transformers
GitHub: https://www.twine.net/signin
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