Fractional AI Platform & Agentic Systems Executive

Scale AI from pilot to production.

I help executive teams build the platform, governance, and operating model required to scale AI into production.

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20+ years in enterprise software · Fortune 500 platform leadership · PMP · PMI-ACP · Dual M.S. in CS/AI & Engineering Management

30–45%
Improvement in RAG Accuracy
$10M+
AI Programs Defined & Funded
99.95%
Uptime in Production Environments
Up to 40%
Reduction in AI Infrastructure Costs

The Questions That Matter

Three decisions every executive team must get right.

? Where should we build vs. buy?
? How do we govern AI at scale?
? How do we turn AI into measurable ROI?
Most teams never answer these clearly. That's why AI initiatives stall.

Capabilities

Core Practice Areas

Executive partnership across platform strategy, governance, security, and production execution.

LLMOps Platform Architecture

Enterprise LLM platforms designed for scale—integrating governance, lifecycle management, evaluation, and deployment into a cohesive operating model that supports production AI.

RAG System Design & Evaluation

Enterprise retrieval platforms built for reliability, observability, and measurable business outcomes—combining hybrid search, evaluation frameworks, and continuous improvement.

AI Agents & Orchestration

Production-grade agent systems that coordinate tools, workflows, and decision-making within defined governance, safety, and operational boundaries—paired with continuous evaluation that catches silent regressions before they reach end users.

AI Governance & Compliance

Governance frameworks that enable safe, auditable, and scalable AI adoption—integrating risk management, model lifecycle controls, and regulatory alignment into platform operations.

Explore all seven practice areas

Who I Work With

Organizations ready to move beyond experimentation.

I work best with teams that have validated AI's potential and now need the platform leadership to make it real.

— CTOs and VP Engineering scaling AI from pilots to enterprise platforms
— Organizations that need governance, security, reliability, and cost control before they can scale AI
— Teams looking for a fractional AI platform leader — not another consulting deck

Why Teams Reach Out

  • "We have working pilots, but no platform strategy to scale them."
  • "Our AI works in demos — but breaks down in production."
  • "We're running agents in production but can't tell when they're quietly failing."
  • "We're spending on AI tooling but unclear what to build in-house vs. buy."
  • "We need governance, security, and compliance guardrails before we can go enterprise-wide."
  • "We're getting bills for AI tool-use but can't tell what's driving cost or value."
  • "We invested in an AI platform, but adoption is stalled and ROI isn't materializing."

What Success Looks Like

Outcomes you can expect at production scale.

Clear, measurable improvements across delivery, reliability, governance, and adoption.

— Deployment cycles compressed from weeks to days
— 99.95% platform uptime across production workloads
— Up to 40% infrastructure cost reduction
— 30–45% retrieval accuracy improvement in RAG systems
— Agent workflows resolving ~40% of tier-1 volume autonomously — with human sign-off on exceptions
— Enterprise governance aligned with EU AI Act, SOC 2, and NIST
— Measurable adoption growth across teams and use cases

Let's Talk

Ready to turn your AI investments into production systems?

If you're working on something that requires deep AI platform expertise, reach out with context on your initiative and what you're trying to accomplish.

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