Principal Software Engineer in Test, leading AI adoption and building developer platforms at scale. I serve on the engineering AI leadership group at Instructure, where I've helped established the vision and roadmap for AI-augmented development across all phases of the SDLC.
- AI strategy & leadership — Shaping company-wide AI vision, standards, and implementation. Founded a monthly AI roundtable for cross-team knowledge sharing and maturation.
- AI skills & agents — Built AI agents that improve documentation, code testability, and test coverage with opinionated guardrails. Reduced project cycle time by 30%.
- AI-powered performance testing — Created skills and agents that cut onboarding time from 3–6 weeks to half a day — reclaiming 42+ engineering weeks of capacity.
- AI-augmented homelab – Using agentic skills to build a simple, secure, privacy-focused home network and lab. Omada, NextDNS, Docker, Traefik, Tailscale, Unraid, Home Assistant.
- MCP – Learning by building an MCP server and typescript library interface to manage my homelab Omada controller configuration with AI agents.
- Zero performance incidents during highest-traffic, highest-risk revenue period across teams following the test strategy I co-created — saving hundreds of thousands in avoided incident costs
- 99.996% uptime on the company's first API gateway through full-pyramid automated testing (functional, performance, reliability)
- 90% reduction in inter-service production incidents after creating and evangelizing the company's first contract testing framework — 85% team adoption in under a year
- Company-wide SLO platform — Designed uptime signaling, monitoring, and reporting adopted across all products. Collaborated with Datadog to develop a new synthetics metric.
