A team, not just a role
They say hire a Marketing Engineer. We say hire a team of them.
Most brands don't need to hire one Marketing Engineer. They need access to a team that already builds, ships, schemas, publishes, and tracks AI visibility every week. That's us.
§01 The role you cannot hire fast
The Marketing Engineer is a real discipline. The hiring problem is the issue.
Profound named the role earlier this year. The argument is sound: a full-stack marketer who builds systems, automates overhead, and invents AI-native channels. Companies including Google and Synchrony have already hired for the title. The work is real and accelerating.
The problem is not the role. It is the math behind hiring it.
Fewer than two hundred named Marketing Engineers exist worldwide today. Loaded annual cost runs €200K to €280K once you account for benefits, tooling, and ramp. One person, working forty hours a week, cannot cover ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews simultaneously, while also producing content, fixing schema, running outreach, and publishing research. The role compresses six disciplines into one job description. That works for a handful of companies. It does not work for most.
There is a faster path: hire a team that already does this work, on a model that is structurally cheaper than one hire, with results in seven days instead of six months.
§02 What we automate
Overhead, killed at the system level.
Marketing Engineers replace meetings with systems. This is the work the team does on every engagement, week in and week out, as a default.
01
Citation share across five AI surfaces
We run a fixed prompt set against ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews every week. Citation share by surface, recommendation rate, and source-pool drift are tracked as time series.
02
Source-pool monitoring and course correction
When a domain enters or exits the cited source pool for one of your golden prompts, we know within seven days. The team responds with content refresh, schema updates, or publication outreach to restore presence.
03
Passage-extraction content engineering
Pages structured for AI extraction look different from pages structured for Google rankings. We rewrite your highest-leverage pages for passage extraction without breaking your existing SEO.
04
Schema and answer-engine surface fixes
FAQ, HowTo, Article, Comparison, Product, and Service JSON-LD applied to the surfaces AI actually reads. Errors caught before they break rich-result eligibility.
05
Third-party publication outreach
AI rarely cites your own site for category-defining queries. It cites third-party publications. We run weekly outreach to publications already in your category source pool.
06
Competitive citation tracking
When a competitor gains citation ground on a query you care about, you see it the same week. We close the gap before it becomes a permanent disadvantage.
§03 What we invent
New ways of marketing, built specifically for AI surfaces.
These do not exist on a traditional SEO agency menu. They are the engineering work that determines whether a brand enters the AI source pool or stays outside it.
Invention 01
Prompt set curation
The 50 to 150 queries that decide whether buyers in your category find you. We map them on day one, instrument them from week one, and they become the source of truth for every measurement.
Invention 02
Reddit and forum positioning
AI heavily cites Reddit and topical forums. We treat them as a primary distribution channel, not an afterthought.
Invention 03
Citation-grade research production
Original data, analysis, and frameworks that publications quote. Each piece designed to enter the source pool AI draws from for the rest of the year.
Invention 04
Recommendation rate optimization
Different from citation share. Recommendation rate measures whether your brand shows up in the AI's actual recommendation set, not just as a passing mention.
§04 Hire a person, or hire a team
The economics are not close.
§05 Who we are
Senior practitioners, no juniors. We built the framework.
Cite Solutions runs on the proprietary CITE™ framework — Comprehend, Influence, Track, Evolve — a continuous operating system for AI visibility. The framework is what every team member uses. It maps to the four phases of every engagement.
We publish the AI Visibility Index, an open research library of over 100 briefs covering generative engine optimization, answer engine optimization, AI citation analysis, and brand authority signals. Each brief is operator-grade. The team uses them on engagements before anyone else does.
No juniors. The smallest engagement we run carries four senior practitioners. The work is the same on every project.
§06 How to engage
Pilot first. Pay only when we hit the goal we agreed on day one.
Our default engagement is a 90-day pilot. You pay €500 per month for tools and APIs, plus your direct media spend. We carry everything else. At the end of month three, if we hit the success metric written into the engagement letter, the pilot converts on a €6,000 success fee and a €2,500 per month retainer thereafter. If we miss, you walk. No further obligation.
We run a small number of pilots at any one time. The terms are deliberately one-sided in the brand's favor, because pilots become named case studies in categories where we are building presence.
§07 FAQ
The questions buyers ask before they engage.
Is the Marketing Engineer role a real job or a Profound marketing term?
Why hire a team instead of one Marketing Engineer?
What does the Cite Solutions team actually do day to day?
Can we engage Cite Solutions for one part of the work and keep the rest in-house?
How is success measured?
How does this compare to hiring a traditional SEO agency or an AEO platform like Profound or AthenaHQ?
Ready to become the answer AI gives?
Book a 30-minute discovery call. We'll show you what AI says about your brand today. No pitch. Just data.