AI Search Roles
The LLM Strategist is a key role in the AI search ecosystem. Learn more about the LLM Strategist role.
The AI search ecosystem includes multiple specialized roles, each optimizing for different systems and outcomes. Understanding these roles helps you build the right team for AI-first visibility.
LLM Strategist
Primary Focus: Designs and runs systems that influence how large language models retrieve, cite, and summarize information about brands, products, or topics across AI answer engines.
Key Responsibilities:
- Design structured data architectures for entity recognition and citation
- Develop retrieval optimization strategies for ChatGPT, Claude, Perplexity, Google AI Overviews
- Create canonical control systems for authoritative source citation
- Track citation rates, retrieval surface area, and entity alignment metrics
Skills Required: Technical SEO foundation, entity recognition systems, data modeling, retrieval optimization, citation mechanics, analytics.
Other AI Search Roles
SEO Strategist
Focuses on search engine rankings and organic traffic. Optimizes for traditional search engines (Google, Bing) using keywords, backlinks, content, and technical SEO.
Key Difference: SEO Strategists target search rankings; LLM Strategists target AI retrieval and citation accuracy.
Technical SEO Engineer
Implements technical SEO infrastructure: crawl optimization, site speed, structured data, hreflang, canonical tags. Works on the technical foundation that enables both SEO and LLM strategy.
Key Difference: Technical SEO Engineers build infrastructure; LLM Strategists optimize how AI systems use that infrastructure.
Content Strategist (AI-Focused)
Creates content optimized for AI comprehension and retrieval. Focuses on structured content, entity clarity, and information architecture that makes content easy for AI systems to process.
Key Difference: Content Strategists create content; LLM Strategists design the systems that influence how AI systems retrieve and cite that content.
Data Engineer (SEO/AI)
Builds data pipelines, structured data systems, and entity recognition infrastructure. Creates the technical systems that enable LLM strategy.
Key Difference: Data Engineers build systems; LLM Strategists design strategies for how those systems influence AI retrieval.
LLM Strategist role overview