Matthew CarlsonAI Solutions Engineer · Forward Deployed Engineer
Madison, Wisconsin
About
AI Solutions Engineer. Former $40M marketing operator.
I build production AI systems for marketing teams, agencies and professional-services firms.
Before AI, I spent 11 years at Duluth Trading running a $40M+ digital marketing budget that drove $200M+ in annual revenue, owning analytics, attribution, paid media and data feeds. That's why every system I build is scoped against hours saved, revenue and risk, and why it ships with tests and a cost model instead of a demo.
Since 2024 I've been building production systems with AI. Today I lead AI strategy and implementation for a marketing agency, where the work covers a 33-agent client-intelligence platform, voice agents, nightly monitoring of every client account, and coding agents that build CRM systems from written specs. I also take on independent engagements, most recently a 30-day website launch and AI roadmap for a healthcare IT consultancy.
Forward deployed
I work as a Forward Deployed Engineer: embedded with your team, in your systems and data, building the solution in your environment and iterating with the people who will run it. The deliverable is a working system your team owns, not a recommendation. What that means in practice →
- Role
- AI Solutions Engineer and Forward Deployed Engineer
- Builds
- AI agents, MCP servers, voice and chat assistants, CRM automation, reporting pipelines
- Background
- 11 years at Duluth Trading running a $40M+ digital marketing budget ($200M+ revenue)
- Current
- AI Lead Consultant for a marketing agency (fractional-CTO scope); independent engagements
- Based
- Madison, Wisconsin; clients across the U.S.
I work from Madison, Wisconsin, with clients across the U.S.
Operator track record
Eleven years on the business side of marketing
Results from Duluth Trading, 2014–2025.
Career
Path
-
Mar 2026 – present
AI Lead Consultant, marketing agency
AI strategy and implementation with fractional-CTO scope: agent platforms, voice AI, CRM automation, reporting and vendor evaluation.
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Jun 2026 – present
Website & AI Consultant, healthcare IT consultancy
Solo website redesign and launch, post-launch operations and an AI automation roadmap.
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2024 – present
Founder, Matthew Carlson Consulting
Custom AI applications, analytics platforms and automation, including SkillEngine and a media mix model platform.
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2014 – 2025
Senior Marketing & BI Analyst, Duluth Trading
$40M+ budget across 15+ channels; analytics, attribution, data feeds, SEO and executive reporting.
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2006 – 2009
Technical Services, Epic Systems
Healthcare software deployments: workflow analysis, requirements and end-user training.
Core competencies
What I bring
- Agentic systems & MCP: multi-agent platforms, skill libraries, orchestration with QA gates
- Voice & conversational AI: dialogue design, knowledge bases, test suites
- CRM & marketing automation: GoHighLevel, HubSpot-class platforms, APIs and webhooks
- Analytics & reporting automation: attribution, incrementality testing, Google Ads scripts
- Full-stack development: Python, TypeScript, React, Supabase, PHP
- AI-ready web & search: accessible builds, SEO, answer-engine and generative-engine optimization
Credentials
- MCP servers in production
- Claude API & skill authoring
- GoHighLevel AI Studio & Voice AI
- Autonomous coding agents
- WCAG AA engineering
- Google Ads certified
- University of Wisconsin–Madison
How I work
Principles that came from shipping, not slides
Gate before you scale
One graded sample and a consistency check cost hours. Regenerating dozens of outputs from a bad source costs days.
Confidence is a field
Every AI-researched fact is labeled verified, derived or needs input, so people know what they can trust.
Verify the agent's boundary
Autonomous builds run only in named test environments, with location checks and API readback every run.
Report where the work happens
Alerts land as tasks in the tool people already use, not in another dashboard they have to remember.
Test suites make demos safe
A voice agent meets a client only after it passes its test cases and the safety regression.
Price build and run separately
Launch, build, maintenance and usage are separate lines, so nobody is surprised later.
Let's talk about what you want AI to run.
A 30-minute call is usually enough to know whether it's worth building.