The Top AI Search Skills Hiring Managers Want (From 1,543 Job Listings)

AI search is becoming part of mainstream SEO hiring. Across 1,543 full-time SEO roles, nearly half mention AI search or AI workflow concepts with dominant terms like LLMs/generative AI, GEO, AI search, AI tools, and AEO. 

It points to a pattern where employers are asking for broad AI search fluency before they ask for platform-specific experience.

We clustered terms into skills buckets and found that measurement is the strongest signal in the dataset, appearing in 79% of roles. 

Hiring managers may be adding AI search terminology to job descriptions, but they still want SEOs who can measure performance and explain changes.

As Josh Peacock explains; 

"Hiring managers use measurement to screen candidates within the first 15 minutes of an interview. It won’t get you hired, but it takes you out of consideration if you don’t have it.”

Implications for your resume

Explicitly define measurement skills in your resume

AI search complicates attribution through zero-click experiences and fragmented tracking. Employers want candidates who can measure AI search performance alongside traditional SEO metrics.

Measurement skills bucket includes:

• Analytics
• Reporting
• Dashboards
• Google Search Console
• GA4
• Performance tracking
• Proving SEO impact

Weak CV language: Experienced in GA4 and Search Console.

Stronger: Built reporting dashboards across answer engines, GA4, Google Search Console, and rank tracking data to monitor content performance, identify traffic losses, and prioritize updates.

Treat content for AI search as a core skill

Content for AI search appears in 48.4% of roles. Hiring managers are integrating AI search into existing content strategy rather than treating it as a separate discipline.

Content for AI search bucket includes: 

• Helpful content
• E-E-A-T
• Content quality
• Content work that supports visibility in AI-generated answers

Weak CV language: Optimized blog content.

Stronger: Updated priority content to improve answer clarity, topical depth, and visibility across traditional search and AI answer experiences.

Show workflow improvements, not tool usage

AI workflow appears in 33.4% of roles. This bucket includes prompt engineering, RAG, vector search, embeddings, and AI-assisted workflows.

The distinction employers are making is between people who use AI tools and those who build repeatable workflows that improve SEO outcomes.

As Daris Benallal, senior recruiter at Search for Hire, puts it: 

"Candidates see AI on a job description and say, 'I use AI all the time.' But when you dig in, it's custom GPTs for ideation. Clients want someone who can build scalable architecture, not just use a tool."

That could mean workflows for:

• Keyword clustering
• Content brief creation
• Reporting
• Content audits
• Competitor research
• Internal linking analysis & recommendations
• Repetitive data cleanup

Weak CV language: I use ChatGPT for SEO.

Stronger: Built AI-assisted workflows that automated keyword clustering, content brief creation, and internal linking recommendation while keeping editorial review in place.

It’s very interesting to see how the requirements for AI search skills increase as you move up the career ladder.

Employers are not treating AI search as a small execution task. They increasingly expect senior SEOs and managers to understand how AI search affects the entire ecosystem.

Entry-level roles focus on execution and fundamentals; senior roles lean into AI search strategy; and manager roles require cross-functional leadership.

The salary ceiling is rising for SEOs who can lead AI search strategy. The roles commanding the highest salaries sit at the intersection of organic search, AI search surfaces, and business outcomes.

The table below highlights the top-paying roles in the dataset. This is a snapshot, not a benchmark. Many roles don't advertise salary, so treat these as directional signals rather than market averages.

A compelling SEO CV must prove you can apply SEO, content, and analytics skills within AI search environments.

Here’s what to include in your resume:

1. Keep the fundamentals, but make them outcome-based

Standard skills like analytics, technical SEO, and structured data remain essential. Add these to your resume, but structured as outcome-oriented descriptions.

• Weak CV language: SEO reporting, content optimization, and technical SEO.
• Stronger: Improved crawlability and indexing across key templates, leading to higher discoverability for priority pages by x%.

Also, make sure you’re adding performance metrics to each of these deliverables, as it ties outcomes to ROI.

2. Include AI-search language, only where you can prove it

The standout terms in the data are:

• GEO
• AEO
• AI search / LLM search
• AI Overviews / AIO
• LLMs / generative AI

You don’t need to stuff them in your SEO resume, only those you can defend.

Weak CV language: Familiar with GEO, AEO, and AI tools.

Stronger: Developed GEO and AEO strategies for priority topics based on answer patterns and source analysis.

3. Show workflow improvements, not tool usage

The candidates who stand out combine SEO fundamentals with AI search awareness and technical application.

“Used ChatGPT” says very little. Hiring managers need to know what changed as a result of the workflow.

Weak CV language: Used ChatGPT for SEO tasks.

Stronger: Built AI-assisted workflows for keyword clustering, content brief creation, and internal linking recommendations

The modern SEO hire is someone who can apply SEO knowledge to an AI search market. They can build with AI, measure the impact, and explain it to a non-technical stakeholder.

Treat the next 6 to 12 months as a skill investment. Experiment with GEO and AEO strategies, document changes, and include evidence to support claims on your resume.