Technology strategist · Systems architect

Building intelligent systems organizations trust and deploy.

Three decades spanning carrier-grade infrastructure, enterprise applications, executive leadership, automation, and accountable AI.

Trace the work Explore selected systems

30+Years building
through change

6Enterprise
system layers

1Constant:
useful outcomes

Operating principle

Technology changes.
Building what lasts does not.

The tools change. The hard parts endure.

Understand the organization. Turn complexity into clarity. Design for real constraints. Build reliable systems that can evolve with the business.

The technologies and responsibilities changed. The operating discipline did not.

Three decades, one practice

From infrastructure to accountable intelligence

Every era builds
on the one before it.

Explore how each generation of technology expanded the scale, responsibility, and operating discipline of the work.

Enterprise networking established the operating discipline everything else would depend on: capacity, redundancy, routing, recovery, and accountability under pressure.

The enterprise system

Infrastructure

Scale teaches discipline.

Verizon and Sprint routed tens of millions of directory-assistance calls through our carrier-grade network each month. We completed each transaction, then returned the caller to the carrier without interrupting the live connection. Meeting 99.999% SLAs through daily operations and live traffic migrations made operational resilience a contractual requirement—not an aspiration.

Applications

Applications turn architecture into work.

Enterprise applications connect architecture to the people, processes, and decisions that move an organization. The strongest simplify complex work while preserving the controls required to operate it responsibly.

Enterprise applications Business systems Global deployments

Data

Trusted data makes better decisions possible.

From actuarial analysis and biostatistics to executive reporting, the discipline is the same: define the right measures, establish trust in the information, and turn complexity into useful decisions.

Analytics Decision support Business intelligence

Leadership

Technology serves a public outcome.

Eight years as Lehigh County CIO expanded the work from systems to public outcomes. Leading technology across more than 60 departments, offices, and bureaus required clear strategy, sound governance, secure operations, capable teams, and reliable delivery. At that scale, trust is not a message. It is the result of keeping commitments.

Executive leadership Technology strategy Digital transformation

Automation

Good systems reduce friction.

At enterprise scale, small manual steps become structural drag. Connecting Power Platform, Microsoft Graph, Entra ID, Power BI, code, APIs, and line-of-business systems turns fragmented processes into a governed operating layer—reducing handoffs and risk while improving data quality, execution speed, and decision-making.

Power Platform Systems integration Identity automation

Intelligence

AI belongs inside the system.

The opportunity is not a chatbot beside the business. It is bounded intelligence inside the workflows, data, and decisions the business already depends on—accelerating execution while preserving human judgment and accountability.

Agentic systems Enterprise AI Production intelligence

Point of view

The practical AI thesis

Intelligence is a layer—not an application or a model.
The system is the product.

A useful AI system knows what it may access, which actions it may take, when a person must decide, and how every action becomes observable. Without guardrails, intelligence is risk. Without auditability, it is difficult to trust. The model matters. The surrounding architecture matters more.

Understand the system

Map the work before choosing the tool: people, process, incentives, data, constraints, exceptions, return, and the cost of failure. Define the operating outcome before selecting a platform.

Close the loop after launch. Validate adoption, performance, business value, and the next opportunity to improve.

Design for operation.

Architecture extends beyond deployment. It defines ownership, support, security, adoption, governance, and what happens on an ordinary Tuesday.

Automate with judgment.

Deterministic automation remains the default. Agentic AI belongs where rules alone cannot do the work. Preserve human oversight for consequential decisions, exceptions, and accountability.

Representative systems

Architecture in operation

The work behind
the interface.

Representative enterprise cases, generalized to protect operational detail. Each begins with the operating problem—not a preferred platform.

Enterprise operations

Employee lifecycle orchestration

Problem: Hiring, access, role changes, and departures were fragmented across identities, applications, approvals, and teams.
Architecture: Microsoft Entra, Microsoft Graph, Power Platform, governed workflows, and event-driven automation.
Scale: Cross-functional lifecycle spanning HR, identity, security, managers, and service owners.
Operational result: Reduced account-creation time from approximately 2.5 weeks to one day while eliminating multiple systems, manual handoffs, and common sources of human error from the onboarding process.
Business value: New employees received access sooner, onboarding became more predictable, and identity provisioning became more consistent and auditable.

Decision intelligence

Executive signal from operational noise

Problem: Leaders had abundant reporting but limited visibility into the exceptions that required action.
Architecture: Connected operational sources, normalized measures, exception logic, and decision-focused reporting.
Scale: Enterprise portfolio spanning multiple systems, owners, and operating measures.
Operational result: Consolidated fragmented operational reporting into decision-focused views of material exceptions, performance variance, and emerging risk.
Business value: Reduced the time leaders spent reconciling reports and allowed attention to shift sooner toward the issues requiring action, with the level of impact varying by solution.

Accountable intelligence

Agentic workflows built for production

Problem: AI could not enter consequential workflows without explicit permissions, guardrails, and accountability.
Architecture: Specialized agents, trusted tools, bounded actions, human judgment, and end-to-end observability.
Scale: Production workflow pattern designed to extend across governed enterprise processes.
Operational result: Automated research, data enrichment, deduplication, analysis, and content generation while preserving human review at consequential decision points.
Business value: Reduced work that previously required approximately 12 hours to minutes, shortened refresh cycles, and created a reusable pattern for introducing AI into governed enterprise workflows.

Enterprise accomplishments

Scale made tangible.

50M+

Calls per month at carrier scale

Led technology supporting directory-assistance services for Verizon and Sprint under a 99.999% availability commitment.

$5M+

Taxpayer savings delivered

Led countywide reassessment and process modernization that produced more than $5 million in public-sector savings.

60+

Departments, offices, and bureaus

Directed technology across a multi-site county organization serving more than 2,000 employees.

250K+

Governed folders provisioned

Built CRM-driven automation that created more than 250,000 SharePoint folders from over 48,000 webhook events.

750+

Enterprise safety users

Designed and delivered a safety application supporting more than 750 colleagues across multi-site operations.

$20M+

P&L oversight

Held responsibility for more than $20 million while leading technology at InfoNXX.

150%

Growth supported in under one year

Scaled technology operations to support 150% growth at Barclays.

Operating record

Evidence at scale

Accountability,
measured.

Across infrastructure, public-sector leadership, automation, and AI, the standard remains consistent: resilient operations, explicit accountability, and outcomes the organization can sustain.

30+Years across infrastructure, leadership, automation, and AI

99.999%Carrier-grade SLA supporting tens of millions of monthly calls

60+County departments, offices, and bureaus served

8Years leading countywide technology as CIO

Current practice / 2026

Testing the edge.
Keeping what works.

Current work centers on production agent workflows, AI-assisted software delivery, enterprise voice systems, and the governance required to connect them safely to real operations.

View professional record

Complex systems. Meaningful outcomes.

Let's turn complexity into
clarity.

If you're modernizing a critical system, connecting AI to operations, or working through a consequential technology decision, I'd welcome the conversation.

Connect with Troy on LinkedIn