LLM Strategist
An LLM Strategist designs and runs the systems that influence how large language models retrieve, cite, and summarize information about a brand, product, or topic across AI answer engines.
- Design structured data architectures that enable accurate entity recognition and citation in AI systems
- Develop retrieval optimization strategies that increase brand visibility in ChatGPT, Claude, Perplexity, and Google AI Overviews
- Create and maintain canonical control systems that ensure AI engines cite the correct authoritative sources
This role exists because AI answer engines (ChatGPT, Claude, Google AI Overviews, Perplexity) have become primary discovery channels. Traditional SEO optimizes for search rankings, but LLM Strategists optimize for retrieval, citation accuracy, and entity alignment—ensuring AI systems understand and reference brands correctly when users ask questions.
- Citation rate increases: Brand appears in 3+ AI answer engines with accurate attribution
- Retrieval surface area expands: Structured data enables AI systems to find and cite 5+ key brand entities
- Entity alignment improves: AI systems correctly associate brand with intended topics and services
What is an LLM Strategist?
An LLM Strategist is a technical role that bridges traditional SEO and AI system optimization. Unlike SEO Strategists who focus on search engine rankings, LLM Strategists focus on how large language models retrieve, process, and cite information.
The role emerged as AI answer engines became primary discovery channels. When users ask ChatGPT "What is [your product]?" or when Google AI Overviews surface your brand, the LLM Strategist ensures accurate retrieval, proper citation, and correct entity alignment.
LLM Strategists work with structured data (JSON-LD, schema.org), entity recognition systems, canonical control mechanisms, and citation seeding strategies to influence how AI systems understand and reference brands.
What does an LLM Strategist do day to day?
Daily work includes:
- Structured data architecture: Designing and implementing JSON-LD schemas that enable accurate entity recognition
- Retrieval optimization: Analyzing how AI systems retrieve information and optimizing content structure for better discoverability
- Citation tracking: Monitoring when and how AI systems cite your brand, identifying gaps and opportunities
- Entity alignment: Ensuring AI systems correctly associate your brand with intended topics, services, and attributes
- Canonical control: Managing which URLs AI systems treat as authoritative sources
- Testing and validation: Running queries in ChatGPT, Claude, Perplexity to verify retrieval and citation accuracy
Skills an LLM Strategist must have
- Technical SEO foundation: Understanding of structured data, schema.org, canonical tags, hreflang
- Entity recognition systems: Knowledge of how AI systems identify and classify entities
- Data modeling: Ability to structure information in ways AI systems can accurately retrieve
- Retrieval optimization: Understanding of how LLMs search and retrieve information from web sources
- Citation mechanics: Knowledge of how AI systems attribute sources and generate citations
- Analytics and measurement: Ability to track citation rates, retrieval surface area, entity alignment metrics
- Technical implementation: Experience with JSON-LD, schema markup, API integrations
Responsibilities → Outputs → Metrics
| Responsibility | Output | Metric |
|---|---|---|
| Design structured data architecture | JSON-LD schemas across key pages | Schema validation rate, entity recognition accuracy |
| Optimize retrieval strategies | Content structures optimized for AI discovery | Retrieval surface area, citation rate |
| Manage canonical control | Authoritative URLs properly marked | Canonical citation accuracy |
| Track citations | Citation reports and analysis | Citation rate, attribution accuracy |
LLM Strategist vs SEO Strategist
How LLM Strategists influence retrieval and citations
LLM Strategists influence AI systems through four primary mechanisms:
- Entity grounding: Ensuring AI systems correctly identify and classify brand entities using structured data
- Structured data execution: Implementing JSON-LD schemas that provide clear, machine-readable information about products, services, and organizations
- Canonical control: Managing which URLs AI systems treat as authoritative sources through proper canonical tags and internal linking
- Citation seeding: Creating content structures that make it easy for AI systems to extract and cite accurate information
For detailed examples, see How LLM Strategists Influence Retrieval and Citations.
What success looks like in 30/60/90 days
30 Days
- Structured data architecture implemented across key brand pages
- Initial citation tracking baseline established
- Entity recognition systems configured
60 Days
- Citation rate increases: Brand appears in 2+ AI answer engines
- Retrieval surface area expands: 3+ key brand entities discoverable by AI systems
- Canonical control mechanisms in place
90 Days
- Citation rate increases: Brand appears in 3+ AI answer engines with accurate attribution
- Retrieval surface area expands: Structured data enables AI systems to find and cite 5+ key brand entities
- Entity alignment improves: AI systems correctly associate brand with intended topics and services
Tools and systems used
- Structured data validators: Google Rich Results Test, Schema.org validator
- Entity recognition systems: Knowledge Graph APIs, entity extraction tools
- AI answer engines: ChatGPT, Claude, Perplexity, Google AI Overviews (for testing)
- Citation tracking: Custom monitoring systems, API integrations
- Data modeling tools: JSON-LD generators, schema markup builders
- Analytics platforms: Custom dashboards for citation rates and retrieval metrics
FAQ
What is an LLM Strategist?
An LLM Strategist designs and runs systems that influence how large language models retrieve, cite, and summarize information about brands, products, or topics across AI answer engines like ChatGPT, Claude, and Google AI Overviews.
What does an LLM Strategist do?
LLM Strategists work with structured data, entity recognition systems, canonical control mechanisms, and citation seeding strategies to ensure AI systems accurately retrieve, understand, and cite brand information.
What skills does an LLM Strategist need?
Required skills include technical SEO foundation (structured data, schema.org), entity recognition systems knowledge, data modeling ability, retrieval optimization understanding, citation mechanics knowledge, and analytics/measurement capabilities.
How is an LLM Strategist different from an SEO Strategist?
SEO Strategists focus on search engine rankings and organic traffic. LLM Strategists focus on how AI systems retrieve, process, and cite information—optimizing for citation accuracy and entity alignment rather than search rankings.
What tools do LLM Strategists use?
LLM Strategists use structured data validators, entity recognition systems, AI answer engines for testing, citation tracking tools, data modeling tools, and analytics platforms for measuring citation rates and retrieval metrics.
How do you measure LLM Strategist success?
Success is measured by citation rate (how often AI systems cite your brand), retrieval surface area (how many brand entities AI systems can find), and entity alignment (how accurately AI systems associate your brand with intended topics).
How long does it take to see results from LLM strategy work?
Initial structured data implementation can show results in 30 days. Citation rate improvements typically appear within 60-90 days as AI systems crawl and index updated structured data.
Do you need technical skills to be an LLM Strategist?
Yes. LLM Strategists need technical SEO skills (JSON-LD, schema markup), data modeling ability, and experience with entity recognition systems. However, the role also requires strategic thinking about how AI systems process information.
Further Reading
LLM Strategist Position in norwich
This LLM Strategist role is available in norwich as a remote position. Team members in norwich contribute to our global AI-first SEO expertise while understanding local market nuances.
We're looking for an LLM Strategist who can help clients optimize for AI answer engines and improve citation accuracy across ChatGPT, Claude, Perplexity, and Google AI Overviews.
Ready to build the future of AI-first SEO?