Founding engineer at enttor.ai, building AI outbound at scale · browser automation, OpenAI pipelines, Instagram/LinkedIn prospecting. Previously founding engineer at Samsam. M.Sc. in deep learning at Uniandes.
Founding engineer, full-stack, deep-learning grad. Short version below; long version over coffee.
K. GÁMEZ · 2026 I'm a software engineer from Bogotá. As founding engineer at Enttor I built the AI outbound engine and browser automation flows for Instagram/LinkedIn prospecting, the Next.js dashboards, the NestJS APIs, and the Supabase + Inngest plumbing that holds it together.
Before that I was founding engineer at Samsam, an e-commerce platform · shopper and merchant apps in TypeScript, React Native, Next.js, Prisma and PostgreSQL. Earlier work crossed data analytics (SQL models, Power BI for HR / risk / operations) and deep learning on satellite imagery for cropland and environmental risk detection.
I finished a B.Sc. in Systems and Computing and an M.Sc. in Information Engineering at Universidad de los Andes, with a specialization in deep learning and a minor in Management. The Game of Life on the right has been alive since 1970; I just gave it a frame.
Everything I've used in production. Coral chips are what I'd pick today, given the choice.
Two founding-engineer tours, a master's in deep learning, and the long stretch at Uniandes that taught me how to ship.
AI outbound engine · browser automation and OpenAI pipelines for Instagram/LinkedIn prospecting, filtering and automated DMs at scale. Full-stack platform: Next.js dashboards, NestJS APIs, Vercel infra. IG/X/Twitter prospecting on Supabase + Inngest with duplicate-detection logic.
Built shopper and merchant apps in TypeScript, React Native, Next.js, Prisma and PostgreSQL. Refactored core services for ~10% lower response times and shipped an alert routing system that pushed critical-error visibility +70%.
Deep learning, computer vision, applied ML · including satellite imagery for cropland and environmental risk detection. Worked as a graduate teaching assistant designing labs and course materials in parallel.
Five years across systems, algorithms, ML and a management minor. Side projects in Python, TypeScript, Java and Swift; certifications in AWS Cloud Foundations and Cloud Developing along the way.
A handful out of many. Each one taught me a different lesson; the lessons compound, the projects compound.
Pipelines that take a brand brief, generate hundreds of ad creative variants, score them with LLM-based aesthetic + brand-fit evals, and deploy the survivors. From founding line to thousands of MAU; the eval pipeline alone runs ~120k judgments a day.
Read the case study →A WebAssembly cellular-automaton sandbox: Conway, Wireworld, Brian's Brain, Lenia. Real-time on a million cells, all running in the browser. The hero on this page uses a sibling implementation.
github →An interactive atlas of escape-time fractals · Mandelbrot, Burning Ship, Julia, Newton · with deep zoom, color schemes, and shareable URLs. A weekend project that ate three weekends.
live →Number-theory walkthroughs as live Jupyter notebooks: Ulam spiral, Goldbach pairs, the Riemann staircase. Used by a few math teachers I admire.
github →The page you're on. Open-source, built incrementally, and a place to put math that I think is beautiful next to software I'm proud of.
github →The numbers, the languages, and the repos. The contribution graph is decorative; everything else is real.
A live snapshot. Updated when something changes; usually every Monday morning.
Not the canon. Just the ones I keep recommending.
I take on a small number of consulting projects per year, plus the occasional collaboration. If something here resonates, the inbox is open.