GTM & AI automation engineer. I design and ship the lead-gen, enrichment, sequencing, and reporting infrastructure that revenue teams run on, then wrap AI agents around it so the machine runs itself.
Track record
Most engineers can build a workflow. I build the full go-to-market system and run it against real client revenue. Here is what that has looked like.
Things I've shipped
Not toy demos. Production systems with real integrations, real users, and real revenue attached. Most run behind client auth, so I'm happy to give a live walkthrough on request.
Real-time Meta ad-spend and lead-attribution dashboard. Pulls cost-per-lead across contact-match tiers (direct / probable / unresolved) so performance teams see exactly what each dollar buys. Deployed on Cloudflare with zero-trust access and CI/CD.
Multi-source B2B lead scraper (Google Maps, Yelp, Yellow Pages, Search) with anti-detection controls, advanced filters, saved presets, and CSV / Excel export. A deployable lead-gen platform, not a script.
A platform of autonomous "AI employees" I built and operate for clients. Each one owns a real role end to end: a GTM employee that sources, enriches, sequences, and drafts replies; an Ads Manager employee that watches spend and flags wasted budget; a reporting employee that compiles client updates. They run on a shared memory and task layer, so they keep working without supervision.
A client-facing reporting dashboard that pulls HeyReach (LinkedIn), Smartlead (email), and Meta Ads metrics into live reports and automated email summaries, with login auth and per-client filtering. Sold to multiple clients and white-labeled to each one's logo and brand colors. It killed the manual weekly reporting that eats every agency's time.
Stack
The tools I use daily to design, ship, and run go-to-market systems.
Contact
Open to US-remote roles in GTM engineering, forward-deployed engineering, and AI automation. Fastest way to reach me is email.