Generative Engine Optimization (GEO) Specialist

Remote job Remote February 25, 2026

Mayflower is a technology company that alters the entertainment industry to a new level of perception and engagement.

We are developing a partner advertising high-load system with a large RPS, convenient and modern interface. We are growing exponentially and successfully implementing new technologies to accelerate this growth and the system as a whole.

Now we look for a Generative Engine Optimization (GEO) Specialist to join our team!

Job Responsibilities

This role focuses on optimizing our digital presence in AI-generated search results, including systems like ChatGPT Search, Perplexity, Gemini, and other LLM-driven answer engines. You will work at the intersection of SEO, content strategy, data analysis, and prompt-layer optimization to ensure our brand, products, and expertise are accurately and prominently represented across generative platforms.

Content auditing & strategy: Identify gaps; rework pages to answer questions directly with concise, factual, Q&A-style sections and clear entities.
Entity & topic modeling: Map our brand, categories, and key pages to the knowledge graph (Organization/Author/FAQ/HowTo where appropriate); ensure on-page text matches JSON-LD.
Structured data & tech SEO: Maintain schema, sitemaps, internal links, canonicalization; ensure age-gated/explicit sections remain indexable and snippet-eligible without violating policies.
Citation earning (digital PR): Secure mentions/links on high-trust sites LLMs tend to cite; maintain a pipeline of publishable data/resources.
Prompt testing & evals: Build a repeatable harness that queries major LLMs across markets/languages, logs sources cited, and tracks our share over time; analyze “why we didn’t get cited.”, "why we didn’t get mentioned"
Crawler access policy: Manage robots.txt and bot allowances (e.g.,
GPTBot/Perplexity/CCBot) for visibility vs. load; measure effects with logs.
Cross-team collaboration: Partner with SEO, content, legal/policy, engineering, and analytics to ship experiments fast and measure impact.
Testing & Iteration: Conduct experiments analyzing how different content structures influence LLM-generated results and track changes in model behaviors and algorithm updates.
Identify and fix hallucinated or outdated entity data about our brand wherever possible through content, citations, and authoritative references.
Analyze competitors that repeatedly get cited by LLMs; reverse-engineer why they were chosen; reproduce/differentiate.