Welcome to The Hero 🗞️. This is approximately a 2.5-minute read.
🤖 The two profiles hiding behind every "AI engineer" req
❌ Why most JDs are sourcing the wrong person entirely
🚀 The one question that fixes the whole search
🔥 Get Access To 200 High-Quality AI / RAG Engineers (not active on job boards)…
TL;DR
Most hiring managers want an AI engineer. Most actually need an AI-powered engineer. These are two completely different searches.
AI engineers build the infrastructure - RAG pipelines, vector databases, fine-tuned models. Rare. Expensive. Most companies don't need one.
AI-powered engineers build with AI. They live in Cursor, Claude, and Copilot-and ship what used to take a team of four.
😅 You're Hiring for the Wrong AI Engineer
Your hiring manager wants a "AI engineer."
The req hits your desk.
You source ML researchers, LLM specialists, people with PhDs and papers.
One weeks later… every candidate is rejected.
"Too academic - we just need someone who can ship product."
The candidates weren't wrong.
Your job description was…
The full breakdown is just below - don’t miss it! 😉
Links of the Day:
🔗 Best Links
Here are some of the best links I’ve found since last time I emailed you:
🗺️ Interview Strategy
Transform Interviewing into Strategic Talent Selection (link)
Interview Training: Best Practices for Hiring Managers (link)
🔎 Find Candidates
7 Recruitment Sourcing Strategies to Find Top Talents in 2026 (link)
Talent Sourcing in 2026: Best Recruitment Strategies (link)
🤖 AI Recruiting Tool
10+ Best AI Recruiting Software for 2026: Expert Reviews + Pricing (link)
AI in Recruiting (2026): What to Automate and What Not To (link)
📰 News
Tech Jobs in 2026: Layoffs, AI Hype, and New Roles (link)
🧙 The Insight
There are two kinds of AI Engineers:
The AI engineer builds the infrastructure - RAG architectures, vector databases, model fine-tuning, custom model deployment.
Research background. Rare. Expensive. Most companies don't need one.
The AI-powered engineer builds products with AI as their primary tool.
Full-stack developers who live in Cursor, Claude Code, and Copilot.
They don't build AI systems-they use them to ship what used to take a team of four.
One writes papers.
The other ships products.
Your hiring manager probably wants the second one - and wrote a JD for the first
Two completely different profiles.
One title.
Get them confused, and the search is dead on arrival.
✅ How to Hire the Right AI Engineer
Start with one question that reframes the entire search:
"Is this person building AI systems - or building products using AI tools?"
The answer changes everything: the title, the comp, the talent pool, the screen.
👉 Find the signal on the profile.
AI engineers have research repos, published models, and Kaggle rankings.
AI-powered engineers ship products, contributed to production codebases, and a tools section that reads like an arsenal - Cursor, Claude, Copilot, v0, Bolt.
If their GitHub is full of deployed apps and their LinkedIn says nothing about machine learning, you've found your person.
Ask:
"Walk me through how you use AI in your daily workflow.”
“Where does it save you time? Where does it break?"
Real ones light up.
They'll tell you how they scaffold an entire feature in Cursor before writing a single line themselves.
Posers give you buzzwords.
👉 Fix the comp before you source.
This isn't a $300K ML researcher.
It's a $130-200K senior full-stack dev who happens to be 10x more efficient than anyone else on the team.
Help your hiring manager see that before you burn budget chasing the wrong profile.
To Sum It Up…
The most expensive recruiting mistake in 2026 isn't a bad hire.
It's making great hire for a job that doesn't exist 😅
And To Wrap It Up…
The most valuable engineer right now isn't building AI…
They're building with it.
Know the difference 🙏
HOW WE CAN HELP?
There are a few ways:
Or you can just reply to this email.
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