I'm a founding Forward Deployed Engineer at Notion, where I built the technical delivery model our team uses to run high-stakes enterprise migrations. I'm also writing The Forward Deployed Engineer's Handbook for O'Reilly, the first definitive guide to the role.

Before Notion I was a Software Engineer at Google and Bloomberg, building certificate authority infrastructure and large-scale data platforms. I've also coached 600+ engineers through career transitions into top companies.

I teach this because I'm doing the job right now, not summarizing it from articles. Everything in my workshops comes from live engagements: real scoping decisions, real security reviews, real stakeholder fights. If you want to break into Applied AI, learn it from the trenches.

I'm the Founding FDE at a venture-backed AI services firm, where I scope, build, and own AI deployments end to end for clients. Before this, I spent five years as an AI Engineering Manager at Accenture, taking AI from prototype to production for Fortune 500 clients: building ML pipelines on GCP and Azure, leading the MLOps and LLMOps practice, and launching a GenAI tool for retail marketing that hit 90 percent adoption.

Before most people knew what a large language model was, I was building with them. I believe the best time to develop real intuition for a technology is before the hype arrives, when you're just solving problems.

Teaching is where I actually light up. I've taught 30+ students per cohort as a data analytics instructor, spent 400+ hours tutoring before that, and now teach practical AI skills to a large online audience. I think expertise should be democratized, and most AI education stays too abstract to ever get used.