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Software Engineer · MSc in Artificial Intelligence

I build production AI systems, open-source research tools, and developer-focused software — with a particular interest in multi-agent AI, LLM/VLM evaluation, retrieval systems, multimodal reasoning, and neural audio. I am based in Tenerife.


What I've Shipped​

Institutional RAG system at Cabildo de Tenerife — one of Spain's largest public institutions:

  • 🏆 Outperformed Microsoft Copilot Studio on document retrieval benchmarks against the institution's own corpus
  • ⚡ Staff now surface institutional knowledge in seconds, not hours
  • 🏗️ Sole AI Engineer — I owned architecture, retrieval pipeline, embedding strategy, LLM integration, and deployment end-to-end
▶ Case study: How I beat Microsoft Copilot Studio

The Cabildo already had access to Microsoft Copilot Studio — an enterprise product with significant backing. My task was to make their internal document corpus queryable by non-technical staff.

I built a custom RAG pipeline from scratch, making independent decisions on:

  • Chunking strategy tuned to the structure of government reports
  • Embedding model chosen for domain fit, not popularity
  • Retrieval architecture designed around the query patterns of the institution's staff

In a controlled benchmark against the same corpus, my pipeline achieved higher precision and relevance than Copilot Studio. A government institution now runs on that system in production.


Research & Open Source​

My current work combines practical AI engineering with independent research and open-source tooling:

  • TrainLens — research-grade notebook reporting for AI training runs, directly inside Jupyter.
  • MAVERICK — cognition-inspired multi-agent visual reasoning built around an auditable perceive → describe → critique → refine loop.
  • Neural Audio Theory — an open educational project explaining the engineering foundations of AI music generation, from signal processing and embeddings to transformers, diffusion architectures, training, and prompt conditioning.
  • music-to-text — local-first audio intelligence tooling that turns audio into structured metadata, A&R notes, PR pitches, playlist descriptions, and sync-licensing copy.
  • LastLight — low-power, offline RAG for disaster guidance, designed around sourced retrieval and confidence-based refusal without cloud infrastructure.
  • edujbarrios-ui — a frontend component library for clean AI interfaces, demos, and developer tools.

I also maintain a growing portfolio of research-oriented Python packages for model evaluation, embedding drift, VLM inspection, RAG chunk auditing, prompt safety, multimodal dataset quality, and text-to-music prompting.


Engineering Approach​

🔍 RetrievalChunking and embeddings chosen per corpus — not per default
🧪 EvaluationModel and pipeline behavior measured explicitly, with reproducible diagnostics
🤖 AI systemsMulti-agent and multimodal workflows designed for auditability, not just impressive outputs
⚖️ Model selectionCost / quality / latency tradeoff, not hype
🏗️ ArchitectureObservable, failure-tolerant, built to iterate
🤝 StakeholdersRequirements → specs → momentum across technical and non-technical teams

Background​

  • 🎓 B.Eng. Computer Engineering (Software Engineering) — Universidad de La Laguna
  • 📄 Thesis: 10/10 — Applied multimodal LLMs to retinal imaging for early glaucoma detection
  • 🎓 M.Sc. Artificial Intelligence — Universidad Alfonso X el Sabio

Where I Work Best​

✅ AI systems that need to move from experimentation into reliable real-world use
✅ Custom retrieval pipelines and RAG architectures built around the actual corpus
✅ LLM/VLM evaluation, multimodal reasoning, and uncertainty-aware workflows
✅ Multi-agent systems where roles, interfaces, and failure modes can be inspected
✅ Developer tools and research infrastructure that make AI experimentation more reproducible


Beyond Engineering​

Electronic music producer EyeMad — 10M+ streams, featured on Spotify editorial playlists Electro Chill and New Music Friday. Building an audience from zero is a different kind of systems thinking: how creative decisions compound over time, and how to ship work that resonates.


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