AI Engineer
Santiago Paz
RAG, agents and multi-agent systems.
Software engineer with 13 years building high-traffic web platforms, now moving into AI engineering. Taking LLMs into production means the retrieval, agents, guardrails and evaluation around the model, not just an API call. Throughout, a recurring thread of visual page builders that turn content models into systems non-engineers can drive.
- Location
- Berlin, Germany — EU work authorization (Italian citizen)
- santiago.paz.1992@gmail.com
- Links
- GitHub · LinkedIn · CV
Selected work
Contract Lens
A deployed multi-tenant SaaS where an LLM extraction pipeline turns PDF and DOCX contracts into typed, structured data that drives a deadline and alert system.
Multi-Agent Trading Desk
12 LLM analyst agents on a LangGraph + FastAPI backend, driving rebalancing and backtesting over a real portfolio, with a Next.js retro-desktop frontend and live broker integration.
bedrock-genai-labs
26 runnable labs against live Amazon Bedrock APIs — a FAISS vector store built from scratch, hybrid dense + BM25 retrieval with reranking, an agent loop written by hand, guardrails, and LLM-as-judge evaluation.
Reddit Idea Miner
A daily pipeline that scans job-search subreddits and Hacker News, extracts actionable product ideas with Claude in a single structured call, and emails a ranked digest.
DiffCV
An open-source CV optimization platform — a structured Master Profile that feeds per-posting CV generation, with a CRM-style application pipeline. Architecture and dashboard built; the AI engine is still in progress.
Reema
A deployed SaaS that adds an embeddable "listen to this article" audio player to blogs and digital media, powered by a multi-provider TTS pipeline.
Pegala
An AI job-search platform for the Argentine market — a resume-tailoring product paired with a companion pipeline that mines job-search communities for product ideas.