SEO / GEO / AEO Specialist

Here is a comprehensive job description for a GEO / AEO Specialist tailored for companies looking to lead in AI-driven search discovery.

Job Description: Generative & Answer Engine Optimization (GEO/AEO) Specialist

Location: [Remote]

Department: Digital Marketing / Organic Growth

Reports To: [CEO]

Employment Type: [Full-Time / Contract]

Role Summary

As search behavior shifts from traditional link-clicking to conversational AI syntheses, we are looking for a forward-thinking Generative & Answer Engine Optimization (GEO/AEO) Specialist.

In this role, you will lead our strategy to ensure our brand, products, and insights are consistently cited, recommended, and accurately represented across AI engines (e.g., ChatGPT, Perplexity, Google Gemini, Claude, and SearchGPT). You will bridge the gap between traditional technical SEO, entity management, digital PR, and semantic content structuring to maximize our clients' Share of Model (SoM).

Key Responsibilities

1. AI Visibility & Benchmarking

• Track, benchmark, and audit brand visibility, citation frequency, and sentiment across major LLMs and AI answer engines.
• Develop custom monitoring frameworks to measure Share of Model (SoM) against key competitors for high-intent industry prompts.
• Identify gaps where AI engines hallucinate, misrepresent brand facts, or omit our solutions from product recommendations.

2. Semantic Content & RAG Optimization

• Structure and optimize content specifically for Retrieval-Augmented Generation (RAG) systems, semantic search, and vector databases.
• Create and format content around clear entity nodes, direct answer blocks, statistics, and expert quotes that LLMs prioritize during extraction.
• Work with content teams to transform existing assets into "AI-ready" formats (e.g., clear Q&A structures, tabular data, concise summary blocks).

3. Entity & Knowledge Graph Management

• Manage and optimize our brand entity footprint across critical knowledge repositories (Wikidata, Google Knowledge Graph, industry-specific directories, Wikipedia).
• Implement advanced nested Schema markup (JSON-LD), including Organization, Product, TechArticle, ProfilePage, and Speakable schemas to establish explicit semantic relationships.

4. Third-Party Citation & Off-Page Strategy

• Collaborate with PR and Off-Page SEO teams to earn brand mentions and backlinks on high-weight sources used as training or retrieval data by LLMs (e.g., Reddit, Quora, industry journals, major news outlets).
• Monitor and optimize third-party review platforms and community discussions to influence the consensus sentiment scraped by AI engines.

Requirements & Qualifications

Must-Haves

• Experience: 2–4+ years in Technical SEO, Digital Marketing, or Content Engineering, with at least a few months actively experimenting with or executing GEO/AEO strategies.
• Technical Understanding: Deep comprehension of how modern AI answer engines work—including RAG pipelines, vector search, semantic embeddings, and information retrieval concepts.
• Entity & Structured Data Expertise: Hands-on mastery of JSON-LD Schema markup, Wikidata editing, and entity mapping.
• Analytical Skills: Ability to build benchmarking methodologies to track non-traditional search metrics (citations, prompt rankings, sentiment shifts).
• Communication: Ability to explain complex AI retrieval mechanics to non-technical stakeholders (content writers, executives, PR teams).

Preferred / Bonus Skills

• Basic proficiency in Python or data extraction scripts (using APIs from OpenAI, Perplexity, or custom scrapers) for automated prompt tracking.
• Experience with specialized GEO/AEO monitoring platforms (e.g., Profound, Peep Strategy, OTTER, or custom LLM evaluation frameworks).
• Background in Digital PR, brand positioning, or ORM (Online Reputation Management).

Key Performance Indicators (KPIs)

• Share of Model (SoM): % of target prompts where the brand is cited or recommended in AI outputs.
• AI Referral Traffic & Conversions: Organic traffic and direct conversions driven by AI answer engines (Perplexity, ChatGPT, Gemini).
• Citation Quality & Sentiment: Accuracy and positivity score of AI-generated brand overviews and product comparisons.
• Knowledge Graph Completeness: Presence and accuracy of entity data across Wikidata, Knowledge Panels, and Schema.