I'm an AI data systems architect based in Las Vegas / Henderson, Nevada. My 20+ years span MIS and IT — computer software and hardware repair, and managing software systems for education, real estate, and small business. Today that foundation drives what I build: intelligent, secure, scalable AI infrastructure.
Applying machine learning and AI to real enterprise problems — from intelligent data systems to security that learns.
Deep expertise in threat analysis, vulnerability assessment, and security architecture across enterprise environments.
Designing and managing cloud-native systems that scale efficiently while maintaining security and reliability.
Building data systems and infrastructure that support complex business operations at scale.
const danny = {
role: 'Technology & Data Systems',
focus: ['Security',
'Cloud',
'Architecture'],
experience: 20+,
build() {
return systems.that(
scale.securely()
);
}
};My path wasn't conventional. In 2012, I was involved in a case at MGM Mirage where I analyzed the casino's player club database system and identified vulnerabilities in their loyalty program infrastructure. While the company initially benefited from my work, the experience gave me something fundamental: a deep understanding of how data moves through enterprise systems, who controls it, and where the weak points are.
Two decades of hands-on MIS and IT: computer software & hardware repair, and managing software systems for education, real estate, and small business.
Casino player club database analysis and loyalty program infrastructure assessment.
Deploying and maintaining full systems — hardware builds, software rollouts, and the day-to-day infrastructure that keeps organizations running.
Scaling that hands-on work — designing, deploying, and supporting complete systems end-to-end.
Leading AI-focused work — applying machine learning to enterprise security, cloud infrastructure, and data systems so organizations build intelligent, future-proof platforms. What is an AI data systems architect? →
Core competencies built over two decades of working across industries and scales — now focused on where AI meets enterprise systems.
Machine learning systems, intelligent data pipelines, and AI-driven security — turning models into production infrastructure that delivers.
Threat analysis, vulnerability assessment, security architecture, and incident response across enterprise environments.
AWS, Azure, GCP — designing cloud-native systems that scale efficiently while maintaining security and reliability.
Database architecture, data pipeline design, ETL processes, and analytics infrastructure for complex business operations.
System integration, API design, microservices architecture, and technology stack optimization for large organizations.
Business intelligence, reporting systems, data visualization, and actionable insights from complex datasets.
CI/CD pipelines, infrastructure as code, monitoring systems, and operational automation for modern tech teams.
Interested in working together? Let's talk about your technology and data challenges.