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THE AI PULSE
RAG Is the Skill Everyone's Hiring For. Most People Haven't Heard of It.
Week of February 3, 2026 · 440,000 jobs analyzed · Issue #1
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New Jobs Tracked
23,847
This week
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Marketing AI Roles
18%
▲ from 16% last month
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This Week's Signal
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RAG topped the skills leaderboard again. Out of 440,000 jobs analyzed, 4,168 explicitly mention RAG. "Prompt engineering" shows up in 389 descriptions. RAG appears 10x more often.
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The pattern is consistent across functions. Employers want people who can build systems that retrieve information and feed it to AI models. That's what RAG does.
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Skills in Demand
| Skill |
Mentions |
Trend |
| RAG |
4,168 |
#1 overall |
| AI Agents |
972 |
▲ growing fast |
| AI Vendor Evaluation NEW |
— |
New entrant |
RAG — The technique for connecting AI models to proprietary data. Shows up in product roles, engineering roles, and increasingly in marketing and ops. If you work with documents, contracts, or knowledge bases, this skill matters.
AI Agents — Autonomous systems that execute multi-step tasks. The job descriptions mention LangChain, tool use, and workflow automation. More about architecting systems than coding.
AI Vendor Evaluation — A new pattern in ops and IT descriptions: "evaluate and recommend AI tools for the organization." Companies are drowning in vendor pitches and need people who can separate signal from noise. No technical skills required, just judgment.
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The AI-Adjacent Premium
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The highest-paying roles in our database aren't "AI Engineer" or "ML Specialist." They're traditional roles with AI requirements bolted on.
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A Marketing Director who can run AI-powered attribution commands $180K–$220K. Without that skill? $140K–$170K. Same title, $40K–$50K difference.
Domain expertise is the bottleneck. AI labs can hire PhDs to build models. What they can't easily find is someone who understands pharmaceutical compliance, or enterprise sales cycles, or supply chain logistics — and also knows how to apply AI tools to those domains. That intersection is rare. Rare commands a premium.
You don't need to become an AI engineer. You need to become the person in your function who actually knows how to use AI tools. Lower bar to clear. Higher return per hour of learning.
Consider: a marketing team doesn't need five AI experts. They need one marketer who understands attribution, one who can prompt for content briefs, one who can build a RAG system for competitor research. Three different people, all "AI-skilled marketers," entirely different skill stacks.
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Right now, "knows how to use AI tools" is a differentiator. In two years, it'll be table stakes. The premium goes to early movers who establish themselves as the go-to AI person in their function. The window is open. It won't stay open forever.
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The Bottom Line
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● RAG is 10x more common than "prompt engineering" in job postings. The skill bar is rising.
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● The salary premium goes to domain experts with AI fluency, not AI specialists learning a domain.
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● "AI vendor evaluation" is emerging as a skill. Companies need people who can choose the right tools.
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● Marketing AI requirements hit 18% of roles, up from 16% last month.
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