I’m a technical SEO leader focused on building the systems that make organic visibility scalable.
For 15 years, I’ve worked across publishers, marketplaces, and Fortune 500 brands, starting with the technical foundations of SEO: large-scale CMS migrations, crawl architecture, structured data, international and enterprise SEO, and the infrastructure required to make enormous websites discoverable and understandable to search engines.
Over time, I moved from executing SEO programs to building the tooling and programmatic systems that operate them. Rather than treating technical SEO as a collection of recurring manual tasks, I build systems that continuously analyze crawl and search data, identify problems, execute changes, manage structured data and entities, and keep technical infrastructure aligned with how search evolves.
The same philosophy now extends to AI search.
AEO and GEO are often framed as a new set of optimization tactics: make your content easier for an LLM to understand, then try to get cited. I take a broader view. If an AI system is deciding what sources to trust, the answer isn’t limited to optimizing the website it visits. Visibility can be influenced by the entire ecosystem of information an AI system encounters—including websites, YouTube, reviews, LinkedIn, publishers, communities, structured data, and other authoritative sources.
So I build agentic programs that operate across that ecosystem: systems for technical SEO, content, search intelligence, entity development, citation discovery, and distribution. The goal isn’t simply to produce more content or automate individual SEO tasks. It’s to build an operating system for organic and AI visibility that can continuously learn, adapt, and execute with far less manual intervention.
That’s the intersection I work in.
Most SEOs understand search but can’t build. Most engineers can build but don’t understand search. I bring both disciplines together—technical SEO strategy and AI systems architecture—to build autonomous systems that turn search expertise into scalable operations.
How I got here
My start in SEO came in 2010 right after graduating college but not how you might expect.
I was home for the summer applying for jobs in commercial real estate and finance, when my younger brother called me into his room to show me a forum website he had built that was earning a few hundred dollars a month from Google Adsense.
My plan had always been to work in Wall Street, until that moment it had never occurred to me the kind of money that could be made online by learning internet marketing.
That very day I asked my brother to teach me WordPress and through resources like Pat Flynn’s Smart Passive Income, I was off to the races building niche affiliate websites and learning the basics of SEO and digital marketing.
Although I was self taught, I was able to land a job at a local wireless service provider as an SEO Specialist where I worked for the next four years securing #1 rankings for competitive keywords including “free cell phone” and “best cell phone plans”.
The best part about this job was that my bosses really believed in learning from the best in the industryand they paid for many courses in SEO, PPC, analytics and social media management. They also paid for me to attend SEO conferences where I got to learn the latest strategies from incredible marketers like Ryan Deiss and Roland Frasier.
After my time there I worked for a couple of local marketing agencies and started my own agency on the side providing SEO, PPC and social media to home services companies.
During this time I learned to work with enterprise level clients and develop the project management, presentation and implementation skills needed to manage SEO campaigns in a large organization.
In 2017, I got my first opportunity to lead a team as the SEO Manager for a holding company that owned a portfolio of well known internet brands.
This was my first time working with websites that had hundreds of thousands of pages which really required me to develop my technical skills to tackle issues like website migration from drupal to wordpress, log file analysis using tools like Botify, and working with developers to improve crawlability by optimizing our site architecture.
I was able to train a content department of over 15 writers on pillar pages, entities and topical authority which led to a traffic lift of over 200k organic sessions per month.
I also had the opportunity to hire and manage an in-house linkbuilding team while developing systems that allowed us to acquire over 100 links per month at less than $25 per link.
This is the most interesting time to be in tech and I’ve never been more excited to leverage AI and machine learning in the SEO and digital marketing industries.
After taking some time off to travel and work on my own passion projects during the pandemic, I was hired by Leaf Group as the SEO Lead for one of their many publishing brands (eHow, LiveStrong, Hunker, OnlyInYourState, etc).
As the lead for a publisher with over 150k articles and 50 new posts per day, I had to learn to do SEO at scale; working with massive datasets and focusing on systems thinking and how to develop efficient workflows and processes.
The project during this time that I’m most proud of was an internal dashboard that replaced a spreadsheet approach to managing our content renovations.
This internal tool was used by a team of 50+ contractors and led to 40% increase in the output of pages renovated per month, as well as a 20% increase in organic traffic.
This was when my interest in machine learning really and AI really took off as I got to work closely with a team of data scientists and engineers to build internal tools that could classify, cluster and implement taxonomies for our content library.
As LLMs became more powerful I started learning how to incorporate them into our SEO processes to help with keyword research and content brief generation.
That brings us to today, where I’ve just graduated from a program in Nocode AI and Machine Learning from MIT, where I learned to use AI and Machine Learning to make data-driven business decisions by understanding the theory and practical applications of supervised and unsupervised learning, neural networks, recommendation engines, computer vision and natural language processing using tools like RapidMiner.
Today, I build:
- Autonomous AI agent systems that run research, content production, and technical auditing
- Generative Engine Optimization that earns visibility inside ChatGPT and Google AI Overviews
- Automation workflows in Make, n8n, and Claude Code that scale SEO without scaling headcount
SEO is moving into the future fast — and I’m building for where it’s going, not just keeping up.