AI Process Engineer
Matthews Real Estate Investment Services · Scottsdale, Arizona
I took Matthews’ AI program from one department to company-wide within four months. I oversee the AI portfolio and build projects for other teams as a collaborator, dedicated support or primary builder.
70+
AI projects in the portfolio
4
months from one department to every department
40
Claude skills and automations shared
50+
employees trained hands-on
Program leadership
- 70+ AI projects created and managed in Linear, each with a portfolio owner, an executive stakeholder, minimum-viable-product milestones, a pilot test group and a planned rollout.
- Company-wide in 4 months: expanded the AI program from a single department to every department.
- ~150 employees supported as their AI resource, from choosing the right tool to writing full specs for new applications.
- 3 roles on every project: collaborator, dedicated support or primary builder, while overseeing everything else being deployed.
- Overlap caught and merged: track the full portfolio across departments so no two teams build the same thing twice.
- AI intake and scoring model: a standardized intake form for every AI request, scored on business value, enablement and risk reduction, feeding one prioritized master list for leadership.
- Monthly AI digest: a progress report for leadership covering every project’s status, blockers, model updates and the efficiencies created.
Builds and automation
- 40 Claude skills and automations shared across departments, plus 80+ internal skills, project specs and instruction sets.
- AI agents and automated workflows that act as digital teammates, built with LLMs, MCP and orchestration tools.
- AI cold-call simulator: ElevenLabs voice AI with LLM scoring, so junior agents practice live scenarios and get structured feedback.
- AI usage and cost dashboard (in build): token costs pulled through MCP into a live web app on Vercel, with a per-person view and admin filtering.
- Private AI models and agentic processes that keep proprietary data secure.
- Every line of code reviewed by a separate AI agent, and every project documented in Linear, Obsidian and GitHub.
Adoption and executive communication
- 50+ employees trained through hands-on sessions, classes and live demos, backed by an internal AI curriculum and learning management system.
- Customer Zero for emerging AI platforms such as Superblocks and Lovable: structured pilots and product feedback to the vendors.
- Platform evaluations of enterprise AI tools including Supabase and Lovable, from fit assessment through vendor follow-up and company rollout.
- Executive-ready presentations and live demos showing leadership where each project stands, what’s new and the working product.
