Software Builder • Argentina → Global
I build things
from zero to working.
Backend engineer with strong product instinct. I design systems, write the code, and make sure the thing actually solves a real problem, not just that it runs.
Building in public, one system at a time.
Who I am
I like building systems that survive reality.
I'm a backend engineer and builder from Argentina with over 15 years of experience. I specialize in systems that process large volumes of messy and unreliable data: large-scale scraping, data pipelines, pricing intelligence, and platforms that need to work under real-world conditions.
I worked closely with the early Mediarails team, a startup later acquired by Impact.com, where I learned what it really takes to build systems that create business value, not just technical complexity.
What drives me is taking an ambiguous idea and turning it into something usable, reliable, and alive in production.
What I do
I build systems that ingest messy, inconsistent data from many sources and turn it into something reliable and useful. That means designing the pipeline, making the hard calls about ambiguous inputs, and shipping something that actually works under real conditions.
I'm comfortable going from idea to working product — not just the engineering layer, but understanding the problem, shaping the solution, and iterating until it makes sense.
How I think
I've spent years turning messy, inconsistent data from dozens of sources into something actually useful. That experience shapes how I approach everything — I've learned to trust nothing at face value, make explicit decisions about ambiguity, and build systems that degrade gracefully instead of breaking silently.
Selected Work
Built end to end — a drop-in Authentication as a Service for indie hackers and startups. One script tag replaces hours of OAuth setup: Google, GitHub, Passkeys, RBAC, MFA and webhooks included. Designed as a cheaper, simpler alternative to Auth0, with a working demo, dashboard, and live pricing.
A SaaS tool that helps websites become visible to AI bots like ChatGPT, Claude and Perplexity. Installs via a single JS snippet — the service analyzes the page, generates a structured knowledge base with semantic contracts and JSON-LD tags, and serves it back to LLM crawlers. Think of it as SEO, but for the AI era.
An ActiveRecord-inspired ORM for Python — built from scratch to understand how the abstraction works, not just how to use it. Convention over configuration, full CRUD, and a clean query interface. The kind of project you build when you want to know what's really happening under the hood.
An ongoing technical investigation into whether a competitive brand protection pipeline is viable as a bootstrapped product. Monitoring newly issued domains via Certificate Transparency logs, combining lightweight heuristics with deeper inspection — rendering sites to extract metadata, content signals, and visual identity elements. Building the infrastructure to find out if it can work at the level of established players.
A global news search engine indexing verified sources from every country in the world —
crawling, processing and indexing new articles every few hours. Detected the user's
country on access and surfaced local news automatically, while supporting cross-country
topic search across all sources simultaneously.
Built on a distributed architecture across 5 AWS servers: one per continent pair
(Americas, Europe/Africa, Asia/Oceania), a dedicated DB server, and an API server.
A single codebase ran on all workers — each processing only its own Sidekiq queue
by continent. Shut down after an unexpected AWS bill wiped out the credits. It had
real traffic. The infrastructure worked.
Started as a local tool to monitor river levels in Entre Ríos, Argentina —
got featured on the front page of the local newspaper twice. Then scaled it
into an international platform integrating river monitoring data from Argentina,
Brazil, Uruguay, Chile, Peru, Italy, Spain, the US, and Paraguay.
The US integration required reverse-engineering several data sources — applied
analysis that bordered on creative hacking. Shut down eventually due to
infrastructure costs vs. low usage, but the technical scope far exceeded
the original ambition.
Price intelligence system tracking 20k+ products across multiple sources. Designed prioritized update pipelines to maintain data freshness under constrained resources. Distributed workers and scheduling strategies to balance real-time needs with cost and performance at scale.
SEO-scale platform indexing over 1M companies. Designed efficient content generation and delivery strategies to serve large volumes of pages while minimizing infrastructure costs and maintaining high availability.
NLP pipeline to extract entities, sentiment and relationships from news data, building a structured knowledge graph for downstream analysis. Transformed unstructured text into connected, queryable data enabling higher-level insights at volume.
Background
It was an excellent school on what really matters when a product goes from MVP to a real business.
After the acquisition by Impact.com, continued contributing to MVPs and proofs of concept, evaluating new tools and technologies.
Built the full stack from scratch: scraping infrastructure, distributed workers, prioritized update pipelines, and the product layer on top.
A good example of making pragmatic tradeoffs based on real usage rather than theoretical correctness.
Let's talk.
Building in public from Argentina. Always happy to talk systems, messy data, or interesting problems. Drop me a line.