I set the direction
and own the judgment that ships it.

The arc

Each role handed me more to own. The climb, in order:

• Healthcare compliance. Led compliance initiatives at Humana (Medicare Advantage), automating audit workflows and data validation under HIPAA and Medicare Parts C and D.
• Quality engineering. Built automated test frameworks and data-model validation. This is the discipline of proving a system does what it claims before it ships.
• Data engineering. Designed and built pipelines, BI, and API integrations for a major public utility (PRASA via TrueNorth), and led data-governance work across its analytics.
• AI and automation leadership at Optum (UnitedHealth Group). I now lead the AI/LLM automation workstream and the migration of legacy systems into modern, ML/AI-driven platforms. An in-house LLM tool I built is in production, automating first-draft BRDs and data-dictionary context. I also designed and taught an Excel-based analytics course that got non-technical supervisors and managers working with data directly.

The throughline is simple. Compliance taught me what “correct” has to mean in a regulated, high-stakes domain. Quality engineering taught me how to verify it. Data engineering and AI leadership are where I set direction and drive delivery now.

Where I work, and who I build for

I’m based in Puerto Rico and build for the PR market first. That means bilingual (EN/ES) products, local data sources, and the Act 60 context that matters to business clients here. Most of my time goes to growing the work and the people around it. I still get hands-on when it counts.

How I deliver, and where the judgment comes in

Here’s the part a resume doesn’t show. Everything in my portfolio (a live real-estate marketplace, a procurement-intelligence product spanning six government data systems, and a business OS running on AWS) I led from architecture to live production, directing an AI-assisted implementation layer.

The AI layer does the heavy lifting on implementation. The leader owns the parts that don’t delegate: strategy, architecture, judgment, verification. That last one is where most of the work lives. A few examples of directing that delivery:

• A 50-agent QA fleet stress-testing the FT-OS business OS.
• A 44-agent gap analysis on the LicitaPR data backend.
• An authorized Nidopr security audit. 21 findings, posture strong.
• A 15-skeptic adversarial test that killed a tempting-but-false finding before it could ship. A less skeptical process would have published it.

That last one is the whole point. AI will happily generate a confident, wrong answer. My job as the person leading is to refuse to ship it until it’s been tested hard enough to break.

The honest line

AI doesn’t replace the team. It multiplies it. It lets a leader get from strategy to shipped product fast, while still owning the architecture, the judgment calls, and the verification that decide whether the work is true. Point me at a team and I multiply what it can ship.

That’s the skill I’m bringing.