SEO Manager (AI Audit)

Role Overview 

We are looking for a Freelance SEO Manager to support the delivery of AI Visibility Audits, a new-generation diagnostic that evaluates how brands are represented, surfaced, and cited across AI platforms such as Google AI Overview, ChatGPT, and Gemini. 

This role goes beyond traditional SEO. It requires the ability to work with search data, prompt engineering, and LLM outputs to generate clear, insight-led recommendations. Critically, it demands someone who can think strategically about what the data means for a brand, not just what it shows, and who can translate complex findings into a compelling story that clients can act on. 

Core Responsibilities 

1  Prompt & Topic Mapping 

This is the foundation of the audit. You will translate category-level research into a structured query map that mirrors how real users interact with AI platforms. 

• Translate Category Assessment outputs into: 

• Topics (approximately 10 per audit) 

• Seed keywords (approximately 20 per topic) 

• Prompts at a 1-to-1 keyword-to-prompt ratio (approximately 200 prompts total) 

• Ensure prompts reflect: 

• Real user search behavior, not keyword lists 

• Informational and decision-based intent in balanced proportion 

• Local language nuances where applicable 

• Audit for duplication, intent drift, and coverage gaps before data collection begins 

2  AI Visibility Data Analysis 

You will systematically analyze brand presence across AI-generated responses, structured across three core dimensions. 

• Run and document outputs across major AI platforms including Google AI Overview, ChatGPT, Gemini, Copilot, and others as applicable 

• Interpret and structure findings across: 

• Visibility: is the brand present in AI-generated responses? 

• Citation: is the brand being named as a source, and how frequently? 

• Sentiment: how is the brand framed when it does appear? 

• Identify patterns across topics and flag the gap between citation presence and actual AI visibility 

• Go beyond surface counts to interpret what the data signals about the brand's authority and narrative positioning in the AI answer layer 

3  Insight Generation & Storytelling 

Data without story is noise. This is where strategic thinking and communication skill matter most. You are not summarizing findings. You are building a case. 

• Identify topic-level performance gaps and prioritize by business impact, not just volume 

• Map competitor positioning in AI-generated responses and articulate what it means for the brand's share of narrative 

• Surface recurring themes in how the brand and its category are described by AI platforms 

• Structure every finding with clear logic: 

• What is happening: the observation grounded in data 

• Why it matters: the strategic implication for the brand 

• What to do next: a specific, actionable opportunity 

• Build client-ready slide narratives that flow as a coherent argument, not a data dump 

• Anticipate client questions and pre-answer them through the structure and framing of the output 

The measure of a strong insight is not how much data it references. 

It is whether a client reads it and immediately understands what to do and why it matters. 

4  Strategic Recommendations 

The audit must end with a clear, prioritized path forward. Recommendations should be specific enough to act on and strategic enough to guide investment decisions. 

• Propose actionable recommendations across: 

• Content strategy: what to create, strengthen, or restructure to improve AI representation 

• Authority building: how to increase the likelihood of being cited as a credible source by LLMs 

• Platform prioritization: where to focus effort based on the brand's current AI footprint 

• Sequence recommendations by effort versus impact so clients can prioritize with confidence 

• Apply query intent prioritization and topic ownership strategy as guiding frameworks for structuring the recommendation set 

• Connect recommendations back to the data so every suggestion is traceable to a finding, not an assumption 

5  Quality Control & Data Validation 

Audit credibility depends on data integrity. You are responsible for ensuring outputs are clean before any insight is drawn. 

• Validate that prompts are non-duplicative, intent-accurate, and structurally consistent 

• Ensure AI outputs are logically categorized and traceable back to the original prompt 

• Ground every insight in observed data and flag clearly where findings are directional versus statistically strong 

• Review final deliverables for internal consistency before client submission 

Requirements 

• Experience: 4+ years in SEO, Search Strategy, or Content Strategy 

• Search fluency: Strong understanding of search intent, keyword behavior, and SERP dynamics 

• Strategic thinking: Ability to interpret data beyond what it shows and articulate what it means for a brand's positioning and decisions 

• Storytelling: Proven ability to structure complex findings into clear, logical narratives that non-technical audiences can understand and act on 

• Analytical rigor: Comfortable working with large datasets including keyword lists, prompt libraries, and LLM output logs 

• Delivery quality: Able to build or meaningfully contribute to presentation-ready outputs with minimal supervision 

• Tools: Proficient in Google Sheets or Excel for data structuring; familiar with SEMrush, Ahrefs, or equivalent SEO research tools 

Nice to Have 

• Experience analyzing AI-generated search outputs across platforms such as Google AI Overview, ChatGPT, Gemini, or Perplexity 

• Understanding of how LLMs retrieve, rank, and attribute sources, not just what they output 

• Experience with prompt construction for research, auditing, or data generation purposes 

• Familiarity with automation approaches for scaling prompt generation or clustering large keyword sets, such as Airops, APIs, or Python-based workflows 

• Multi-market or localized SEO experience, particularly across APAC markets 

What Good Looks Like 

The right person for this project understands that AI visibility is not a ranking problem. It is a representation problem. Brands are not missing from AI responses because they lack links. They are missing because they have not built the kind of content and authority that LLMs recognize as trustworthy, citable, and relevant to user queries. 

A strong candidate will approach the audit the way a strategist would: starting from what the user actually asks, mapping where the brand currently sits in the answer, identifying the gap, and building a clear, prioritized case for how to close it. They know that the quality of their thinking is visible in the structure of their output, and that a well-told story is as important as a well-analyzed dataset. 

This is not a traditional SEO audit. You are not reviewing title tags or crawl errors. 

You are evaluating a brand's presence in the answer layer and building the strategic case for how to strengthen it. 

Engagement Details 

• Type: Project-based freelance 

• Scope: Single client audit; potential for ongoing engagements based on performance 

• Location: Remote; APAC market familiarity preferred 

• Collaboration: You will work closely with the lead SEO strategist and account team throughout delivery