
Ernesto Vizcaíno
Product Engineer — AI, Fintech & SaaS
I build and launch full-stack products from zero to production. I’ve founded SaaS products, built fintech and AI systems, and shipped mobile software used by thousands of people.
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Experience
I take products from initial concept to real users, combining engineering, product decisions and a close understanding of how the software performs in practice.
Founder / Product Engineer atKashi
Designed and built an offline-first POS for small businesses across mobile and web, including inventory, sales, customer credit, reporting and cross-platform subscriptions.
Founder / Product Engineer atPasaEGEL
Founded and built an EGEL preparation platform end to end, including interactive simulations, payments, analytics and SEO. Reached 300+ users, 5,000+ monthly visitors, 130+ paid orders and top-five Google rankings, driven primarily by organic search.
AI Engineer / Founding Team atFinanciamiento Inteligente / Xignus
Built a credit pre-approval system that supported more than $4M MXN in SMB financing during its first month, alongside AI agents and financial dashboards built with React and Python.
Technical Co-Founder atOliver AI
Led engineering across a fintech platform and production AI workflows for loan origination, risk analysis, compliance and document processing.
Founder / Engineer atOliver POS / ERP
Built and launched a React Native POS app that reached 10,000+ downloads and 3,000 active users within three months, then expanded it into a complete web ERP.
Selected work
A selection of products and research that represent my approach to engineering, product development and problem-solving.
- KashiOffline-first POS for small businesses, combining sales, inventory, customer credit and reporting across mobile and web.
- PasaEGELEGEL preparation platform with interactive simulations, study modules, payments, analytics and an organic SEO acquisition engine.
- Oliver AIProduction AI workflows for financial services, covering loan origination, risk review, compliance and document analysis.
- Gaia–OGLE Star ClassifierMachine-learning classifier trained on 137,258 variable stars across 11 classes, achieving a 0.9847 weighted F1 score against OGLE labels.
Stack
Writing
Contact
I’m open to product engineering opportunities, ambitious startup teams and selected collaborations.

