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- Tasks: Design and optimise systems for AI to accurately retrieve and cite brand information.
- Company: Join a forward-thinking tech company at the forefront of AI innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Be a key player in shaping how brands are understood by AI systems.
- Qualifications: Technical SEO knowledge and experience with structured data and entity recognition.
- Other info: Dynamic role with rapid advancements in AI technology and career progression.
The predicted salary is between 36000 - 60000 £ per year.
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
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.
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.
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
| Aspect | SEO Strategist | LLM Strategist |
|---|---|---|
| Primary Goal | Rank #1 in search results | Accurate retrieval and citation in AI systems |
| Key Metrics | Organic rankings, click-through rate, traffic | Citation rate, retrieval surface area, entity alignment |
| Primary Tools | Search Console, keyword tools, backlink analyzers | Structured data validators, entity recognition systems, AI answer engines |
| Time Horizon | 3-6 months for ranking improvements | 30-90 days for citation and retrieval improvements |
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
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
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.
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.
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.
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.
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.
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).
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.
LLM Strategist in Norwich employer: Neural Command, LLC
Contact Detail:
Neural Command, LLC Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land LLM Strategist in Norwich
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the AI and SEO space. Attend meetups, webinars, or even just chat with people on LinkedIn. You never know who might have a lead on your dream LLM Strategist role!
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your experience with structured data, entity recognition, and citation tracking. Use real examples to demonstrate how you've optimised retrieval strategies. This will make you stand out when you apply through our website.
✨Tip Number 3
Practice makes perfect! Run some test queries in ChatGPT or Claude to get familiar with how AI systems retrieve and cite information. This hands-on experience will give you an edge in interviews and show that you're serious about the role.
✨Tip Number 4
Stay updated! The world of AI is always changing, so keep learning about the latest trends in LLMs and structured data. Follow industry blogs, join forums, and engage with the community. This knowledge will not only help you in interviews but also when applying through our site.
We think you need these skills to ace LLM Strategist in Norwich
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the LLM Strategist role. Highlight your experience with structured data, entity recognition, and retrieval optimisation. We want to see how your skills align with what we’re looking for!
Showcase Your Technical Skills: Don’t hold back on showcasing your technical SEO foundation! Mention your familiarity with JSON-LD, schema.org, and any relevant tools you’ve used. We love seeing candidates who can bridge the gap between traditional SEO and AI system optimisation.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points where possible to make your achievements stand out. We appreciate a well-structured application that’s easy to read!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re keen on joining the StudySmarter team!
How to prepare for a job interview at Neural Command, LLC
✨Know Your Structured Data
Familiarise yourself with JSON-LD and schema.org before the interview. Be ready to discuss how you would design structured data architectures that enable accurate entity recognition. This shows you understand the technical side of the role.
✨Demonstrate Retrieval Optimisation Strategies
Prepare examples of how you've previously optimised content for AI systems. Discuss specific strategies that increase brand visibility in platforms like ChatGPT and Google AI Overviews. This will highlight your practical experience in retrieval optimisation.
✨Showcase Your Analytical Skills
Be prepared to talk about how you track citation rates and measure retrieval surface area. Bring examples of metrics you've used in past roles to demonstrate your ability to analyse and improve entity alignment and citation accuracy.
✨Understand Canonical Control Mechanisms
Brush up on canonical tags and how they influence which URLs are treated as authoritative sources. Be ready to explain how you would manage these mechanisms effectively, as this is crucial for the role of an LLM Strategist.
