I'm a Marketing Operations and Growth Marketer. I build the infrastructure that turns spend into pipeline, pipeline into revenue, and answers the question every CEO asks: which campaigns are actually working?
Most teams split strategy, systems, and execution across three people. I run all three, and I use AI to run them at a scale one person shouldn't be able to reach.
I build the CRM architecture, lead scoring, attribution, and dashboards that let leadership answer "which campaigns produce revenue?" with a real number instead of a shrug. HubSpot from scratch across 5,000+ contacts, €625K+ pipeline tracked to source.
Autonomous agents that audit ad accounts every morning, tools that answer analytics questions in plain English, and content engineered to be cited by ChatGPT and Perplexity. AI as infrastructure, not as a chatbot shortcut.
Paid campaigns across Google, LinkedIn, Meta, and Microsoft, with ICP research, structured A/B testing, and CRM architecture underneath so every lead is scored, routed, and attributed. +25% QoQ MQL growth, 15–20% conversion lift.
Every project below is real, in production, and built end to end. The number on each card is the business outcome, not the tool I used to get there.
Fifteen forms, thousands of views, and 94% of contacts attributed to "unknown source." Leadership couldn't say which campaigns were working. I rebuilt tracking from the ground up, ranked every conversion path by actual performance, and built dashboards that let the team predict pipeline instead of estimate it.
Ran the full demand gen function: ICP research turned into targeting, landing pages, and messaging; structured A/B testing as a system not a one-off; CRM architecture underneath so every lead was scored, routed, and attributed. Covered Google, LinkedIn, and Microsoft Ads simultaneously.
When buyers ask ChatGPT or Perplexity for a recommendation, the brands cited in the answer win. I restructured the website's content so AI engines could trust and quote it, tracked citation and sentiment scores weekly in HubSpot, and reached category leadership in a month.
Budget leaks compound quietly. By the time a human catches a CPL spike or a fatiguing creative, the damage is done. I built an autonomous agent that reviews Google, Meta, and Microsoft Ads every morning, flags issues, summarises performance, and recommends stronger ad angles — posted to Slack at 9:00 AM.
Led a 4-person team through a 4-month rebuild. 15+ lead magnets placed by buyer journey stage, intent-based pop-ups, a qualifying chatbot, and all 18 pages rewritten around ICP pain points. Launched at a 92% SEO score with zero broken links.
Every form submission hit everyone's inbox. Webinars required manual intervention at every step. I built a conditional routing system that sends each query to the right specialist, and end-to-end webinar automation from registration to reminder email — no human steps required.
Real analytics questions don't fit pre-built dashboards. I built a connector that links website traffic and search data directly to an AI assistant. "Which pages lost clicks after the last update?" takes 20 minutes by hand. It now takes one question.
Manual lead research is slow and inconsistent. I built a pipeline that enriches every inbound contact with company data, scores ICP fit automatically, and routes high-fit leads into the right HubSpot nurture sequence — sales talks to the right people from the start.
Three interconnected automations: every new blog post promoted on LinkedIn automatically, every LinkedIn lead traced back to the exact ad that produced it, and every brand mention on Reddit flagged in Slack in real time — 4–5+ conversations caught daily that would otherwise be missed.
Three systems designed, built, and open-sourced. Anyone can install them. These show what I build when I'm not solving someone else's problem.
A scheduled agent that scrapes Meta and LinkedIn ad libraries for a set of tracked competitors, classifies each creative's angle and hook with Claude, and publishes a branded weekly digest. Catches what competitors start saying before your team notices.
View on GitHubA modular SEO operations system. Nine specialized agents handle competitor analysis, content strategy, technical SEO audits, and weekly performance reporting. Auto-setup onboarding configures the system to any company's brand and tools in minutes.
View on GitHubA chained set of Claude skills that takes a keyword to a publish-ready first draft in about ten minutes — voice-matched to your writing, AEO-optimized for AI search, with every intermediate step saved so you can fix the one part that needs work instead of starting over.
View on GitHubEverything here has been used to build something in this portfolio.
Based in Dublin, open to relocating to Canada. Open work permit, no sponsorship needed. If you need someone who can architect the CRM, deploy the AI agents, write the copy, and defend the numbers, I'm one email away.