My path into enterprise engineering started with Sitecore — one of the most complex CMS platforms in the industry. Working on it taught me that frontend development at scale isn't just about components and pages; it's about data architecture, rendering strategies, deployment pipelines, and the tradeoffs between them.
Over four years across Accenture, SkillianTech, Eviden, and Vertis Digital, I've worked on some genuinely hard problems: migrating a legacy Sitecore XP + Commerce stack to XM Cloud + OrderCloud while replacing a monolithic .NET/React architecture with a composable Next.js + NestJS system — with zero feature regression and measurably improved performance.
I'm particularly drawn to the intersection of architecture decisions and developer experience. Good architecture should make your team faster, not slower. A well-structured multisite Next.js application, a clean headless CMS schema, or a thoughtful API orchestration layer can compound engineering productivity for years.
More recently, I've been exploring what it means to be an AI-native engineer — not using AI as a shortcut, but as genuine augmentation. From architecture discussions with Claude to GitHub Copilot for synthesis, to local LLM experimentation with Ollama. The engineers who figure out how to work with AI as a pair programmer will build significantly more than those who don't.