Technical work

Executive perspective.
Practitioner’s depth

Selected systems that demonstrate how architectural decisions connect to revenue, operating speed, guest experience, and enterprise scale.

Why the details matter

Technical fluency improves executive decisions

My leadership perspective was shaped by years designing and delivering production systems, not observing them from a distance.

That foundation gives me a practical understanding of where abstractions break, how architecture influences economics, and why standards must help teams deliver rather than slow them down. I selected the examples below not simply for their technology, but for the business capability each system enabled.

Selected architecture

Cloud-native off-premises dining

Architected a .NET Core, Angular, and Azure microservices fleet management and order tracking platform for real-time restaurant operations across Outback Steakhouse, Carrabba’s, and Bonefish Grill.

Supported nearly 30% of total company sales
.NET CoreAngularAzureMicroservices

The platform supported Outback Steakhouse, Carrabba’s Italian Grill, and Bonefish Grill, connecting cloud-native engineering directly to a new, strategically important off-premises sales channel and enabling delivery fleet management, order tracking, and reporting capabilities.

Selected architecture

Enterprise event-driven architecture

Designed a real-time operating backbone with Azure Event Grid, Functions, and Service Bus for order tracking and curbside guest experiences.

13,000+ PCI devices updated in under 60 minutes
Event GridAzure FunctionsService BusEDA

The same event-driven foundation supported real-time order visibility and a Service Bus orchestration framework capable of coordinating estate-wide device and schema change.

Selected architecture

Last-mile delivery API

Built an Azure Service Fabric API that dynamically enabled third-party delivery outsourcing based on demand economics.

Flexible capacity with optimized delivery cost
Service FabricAPI designCloud architecture

The API created operating flexibility: third-party delivery capacity could be introduced dynamically when demand economics made outsourcing more effective.

Selected architecture

High-performance promotion engine

Engineered complex online-order promotion validation using the Command Pattern and Dapper Async ORM.

Complex validation executed in under 300 ms
Design patternsDapperAsyncPerformance

The design combined the Command Pattern with asynchronous data access to keep complex business rules modular without compromising the response time expected in an ordering journey.

Selected architecture

Applied AI for productivity and guest insight

Established the strategy, governance, and data foundation for AI-powered capabilities that improved team productivity and translated guest feedback into actionable operating insight.

Reduced a weeks-long content workflow to days with fewer than five people
Applied AIDatabricksGuest analyticsAI governance

The work combined a modern Databricks Lakehouse foundation with an enterprise AI roadmap and governance. Applied capabilities helped support four consecutive quarters of year-over-year gains in operator performance and guest-experience scores.

Engineering at scale

Standards that increase confidence and speed

I established enterprise development standards and CI/CD practices that included mandatory unit testing with more than 95% code coverage. The objective was not process for its own sake. It was about creating reliable feedback so teams could change critical systems with greater confidence.

That same philosophy connects my technical and executive work: build clarity into the system, shorten the distance between decision and feedback, and make quality part of the operating model.

Continue exploring

Production depth and current hands-on practice