Nacho Platas is a Staff Engineer based in Madrid with over a decade building robust data platforms across healthcare, retail, and CPG, now focused on operationalizing LLMs and agentic systems. He combines classic Big Data craftsmanship—scrapers, ETL, SQL-on-everything and data-versioning—with production ML patterns like RAG, provenance-aware grounding, and deterministic policies to make model behavior auditable and reliable. At Veeva and Nextail Labs he led platform initiatives using DeltaLake, Trino, Snowflake, DBT and Dagster, and introduced DataContracts and lakefs for governance and reproducible pipelines. He emphasizes measurable operational guarantees (SLOs, cost/latency budgets, retries-with-critics) and designs multi-context grounding that preserves freshness and lineage. An AI enthusiast with a telecommunications engineering background, he writes about production patterns for tool-using agents and pragmatic ways to stress-test fundamentals so speed converts into trust.
10 years of coding experience
10 years of employment as a software developer
Master's degree, Computer Science, Master's degree, Computer Science at Sapienza Università di Roma
Master of Engineering - MEng, Telecommunications Engineering, Master of Engineering - MEng, Telecommunications Engineering at Universidad Politécnica de Madrid
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