I design and deploy AI decision systems for complex environments where context, uncertainty, human behavior, and consequences matter. I combine AI engineering, product strategy, causal inference, simulation, and optimization to turn ambiguous problems into executable systems.
I bridge customer problems, executive priorities, product strategy, and engineering execution. My work spans discovery, problem framing, architecture, prototyping, software engineering, evaluation, observability, governance, and production deployment.
I build closed-loop decision systems that observe, interpret, predict, decide, intervene, measure resulting states, and update their models. I focus on systems that can support descriptive, predictive, prescriptive, and preventive decision-making.
I use econometrics, behavioral science, machine learning, and experimentation to understand causal drivers and changing human behavior. I model uncertainty, simulate outcomes, evaluate trade-offs, and identify interventions that can improve a system's trajectory.
I have led AI strategy, product, operations, and commercial initiatives across fleet intelligence, enterprise portfolio management, biotechnology, real estate, customer experience, and enterprise technology. My experience includes work with organizations such as Microsoft, Oracle, SAP partners, Emplifi, Sciforma, and Métrica Móvil.
I am particularly interested in production-grade AI architectures involving LLMs, multimodal AI, agents, RAG, event-driven systems, evaluation, provenance, reliability, and governance. I also conduct public research and build practical AI decision-intelligence systems.
