Computer Science, University of Florida (B.S./M.S.). Solo founder building and forward-deploying AI systems into small and mid-sized businesses — the messy, real-world integration work between "the model can do this" and "it's running in production for a paying customer."
What I actually do: discovery → architecture → deployment → owning the outcome. Bilingual (EN/ES) AI voice systems, sales-ops automation, and the CRM/data plumbing that makes them stick.
- AI automation for SMBs — voice agents, automated ops, CRM integration. Running in production for real businesses, with the deployment engine public (dma-deploy-kit).
- QuantLab — quantitative research engine: strategies, backtests, a pre-registered risk framework, and paper-trading harnesses. Rigor over hype.
- Robotics mission tooling (UF / CogAbility) — Webots RL teaching systems for students.
Deep: applied AI deployment (LLM orchestration, voice, integration). Broad: Python · TypeScript · C++ · Docker · AWS · Linux · FastAPI/Django · Next.js · NumPy/PyTorch
- dma-deploy-kit — config-driven deployment kit for bilingual Retell voice agents — YAML per client, plan/apply with lockfile idempotency, consent-gated post-call SMS, and a four-layer eval harness (static · transcript · latency · citation-enforced LLM judge) with a golden fixture CI gate and prompt-fingerprinted regression detection. 196 tests.
- pipelinepulse — deterministic deal-scoring + Claude-written daily digest, shipped on a schedule
- quantlab — documented quantitative research infrastructure
- cs foundations — from-scratch implementations: gradient descent, data structures, multi-language coursework
Open to: forward-deployed / applied-AI engineering · automation consulting · serious technical collaboration.