150K users run my code every day.
None of them know it exists. That's the point.
Mexico City · Remote
A dashboard that takes 8 seconds to load is a bug nobody calls a bug. I've spent years hunting exactly those.
I worked as a Senior Engineer at Ubidots, an IoT platform with 150K+ users and millions of real-time events. Outside of code, I'm a speaker, mentor, and published author at IEEE Xplore.
Published research in IEEE Xplore on security in decentralized blockchain systems.
Admission by selection process
Appointment automation SaaS for small businesses: white-label booking pages, zero-login client portal for rescheduling and cancellation, automated email and SMS reminders, and an AI scheduling agent for WhatsApp. Stack: Next.js 15, Supabase, Vercel Edge, Stripe, Twilio, and OpenAI.
Real-time document pipeline monitoring dashboard to track documents through multi-step processing stages (pending → extracting → validating → indexing → done/failed). Includes batch actions, live notifications, and SSE streaming.
Public technical notebook built with Astro where I publish systems research, architecture decisions, runtime analysis, and frontend performance notes.
Production back-office platform I designed and built from scratch to manage freelance and side-project operations. Covers custom web analytics with event tracking and dashboards, a URL vault with one-time secret sharing, client brief management, and automated deployment hooks with live output streaming. Built on Astro, PHP, Node.js, and MySQL — self-hosted on a VPS with Tailscale-protected admin access.
React Native app in production since October 2023, available on iOS and Android. 500+ Android users, 170 iOS users. Built for the Parish of Mixquiahuala to bring the Gospel and teachings closer to the community.
Talks at Frontend, AI and Open Source events.
I support developers' growth in tech communities — online and in person, from 1:1 sessions to group settings at events.
60+ members, ~20 technical events organized.
Decentralized blockchain-based messaging system using public-key cryptography (aes128-ctr). Analyzes key architectural vulnerabilities — 51% attacks, double-spending, and verification speed — and proposes solutions applicable to any blockchain network. Presented at an international conference.
Kernel Ridge model to predict COVID-19 contagion trends in Mexico. Trained on Johns Hopkins CSSE data from the first 50 days of the outbreak to estimate the following 150 days. Implemented in Python with sklearn.
Looking for full-time remote positions. Open to community tech talks at no cost.