01
There is an AI opportunity, but no path to production.
I turn a promising use case into an architecture, a working implementation, an evaluation plan, and an operating model people can trust.
Applied AI architecture and implementation
I work forward deployed: close to the operators, customers, data, and code. I can own the build directly, shape the architecture and team around it, or step in as fractional or interim technology leadership.
Greater Boston and remote.
The job is not to deliver a recommendation. It is to make the problem concrete, build what matters, and leave behind working technology and a stronger organization.
Where I enter
I am most useful when business urgency, technical ambiguity, and organizational friction have become the same problem.
01
I turn a promising use case into an architecture, a working implementation, an evaluation plan, and an operating model people can trust.
02
I untangle architecture, stalled execution, security debt, vendor sprawl, and unclear ownership without losing sight of the business outcome.
03
I create clarity through a transition, turnaround, acquisition, or leadership gap, then build the capability and hand it back stronger.
The work, not just the advice
Personally built
Products and prototypes built close to users, from workflow discovery and system design through code, integrations, evaluation, and deployment.
Architected
Product, data, cloud, security, and AI choices made as one system, with the controls and operating model required to keep it useful.
Team-led
Product, engineering, analytics, cloud, and security teams aligned around clear decisions, accountable ownership, and measurable operating outcomes.
Applied AI proof
The applied AI work includes a commercial voice product with real calls and real payments, a healthcare AI prototype, and an agentic operations system in development. Every project is labeled by its actual maturity.
Explore applied AI workAI phone reference checks for landlords.
Voice biomarker screening architecture.
Agentic operations triage.
Evidence under pressure
Healthcare is evidence of rigor, not a boundary on where I work.
I have led technology across payer and provider healthcare and took three clinical AI applications to production in a HIPAA-governed oncology environment, with human oversight, governance, observability, and operational support.
The same discipline applies wherever software must earn trust: analytics leaders act on, security and compliance that hold up, and systems that operators can actually run.
How I lead
High standards and genuine care are not opposites.
I first learned to lead in the Army, commanding a company in support of forces overseas. The lesson held: give capable people clarity, context, trust, and accountability, and they will accomplish difficult things together.
I stay technically engaged because technical fluency sharpens executive judgment. Whether I am writing code, shaping an architecture, or leading the organization, the standard is the same: solve the business problem and leave the team more capable.
Background
My path runs through software engineering, product, cloud, security, analytics, and operations. I have sat in most of the chairs: developer, product manager, consultant, VP of engineering, founder, and CTO. That range helps me see the whole problem and move between strategy and implementation without a translation layer.
Let's talk
If the path from business need to working technology is unclear, let's make it concrete.