Dear Hiring Manager: You think there's a talent shortage. The data shows you just can't recognize talent when it applies.
You keep posting the same job, interview after interview yields mediocre candidates, and you're convinced "there just aren't enough good engineers out there." But here's the uncomfortable truth: great engineers are applying to your jobs. You're systematically filtering them out because evaluating software engineering talent at scale is nearly impossible—and most companies don't realize how badly they're failing at it.
Here's the fundamental problem: the things that make great engineers great don't show up on resumes. You're scanning for keywords, company names, and years of experience, but 94% of employers using skills-based assessments agree they're more predictive of job success than resumes.
Think about what actually matters for engineering performance: problem-solving creativity, code quality, system design thinking, debugging skills, learning velocity. Now look at your typical resume. You'll find none of these—just a list of technologies, previous employers, and education credentials.
The best engineer you could hire might be a self-taught developer who's been contributing to open source for years, or a career changer who brings unique problem-solving approaches from another field. But your resume filters eliminate them before human eyes ever see their application.
When surveyed, firms expect from new hires:
But here's what experience requirements actually measure: how long someone has been employed as an engineer, not how good they are at engineering.
Most postings requiring specific experience wanted 4–6 years (11% of postings) or 2–4 years (9.6% of postings). Yet over two-thirds of job postings didn't mention any experience requirement at all—suggesting even you aren't sure what you actually need.
The dirty secret? A brilliant engineer with 2 years of experience often outperforms a mediocre engineer with 10 years. Experience correlates weakly with actual engineering ability, but it's easy to filter on, so that's what everyone does.
Meanwhile, just 15% of qualified candidates typically have the latest technology requirements you're demanding. You're optimizing for people who happened to work at companies using specific tools, not people who can learn and master new technologies quickly.
43% of HR professionals consider candidate screening to be the most challenging aspect of their job, and here's why: most technical interviews are terrible proxies for actual engineering work.
The best engineers—the ones building complex systems, architecting scalable solutions, debugging production issues—often struggle with whiteboard coding puzzles that have nothing to do with their actual expertise.
Here's what your typical hiring process optimizes for:
You think you need more applicants, but the data suggests otherwise. Over two-thirds of job postings didn't mention specific experience requirements, indicating companies aren't even clear on their needs. The problem isn't candidate volume—it's that you can't distinguish great engineers from mediocre ones in your current process.
Consider this: 90% of candidates see skills-based hiring as fairer and more effective at showcasing abilities. The engineers who prefer skills-based evaluation are likely the ones confident in their actual abilities rather than their resume credentials.
You're using AI to solve a problem you don't understand—how to evaluate engineering talent—and the AI is just scaling your existing biases.
Meanwhile, the engineers who understand AI well enough to be skeptical of AI hiring systems are probably the ones you most want to hire.
The fundamental challenge is that great engineering work is complex, creative, and contextual—but your hiring process needs to be fast, standardized, and scalable. These requirements are fundamentally at odds.
Real engineering involves:
Your interview process involves:
👉 The skills barely overlap.
Here's the kicker: 49% of employed job seekers believe AI recruitment tools are more biased than human counterparts, and they're actively avoiding companies with obviously flawed hiring processes.
The engineers you most want to hire—the ones who are currently employed, successful, and selective about opportunities—are the least likely to tolerate broken hiring experiences. They have options. They can be picky. And they're choosing companies that demonstrate they understand how to evaluate engineering talent properly.
While you're struggling with resume screening and algorithmic interviews, smarter companies are implementing better evaluation methods:
72% of engineers would consider remote jobs, meaning companies offering flexibility and better evaluation processes can access talent pools you can't reach.
You don't have a talent shortage problem. You have a talent recognition problem.
The great engineers exist, they're applying to jobs, and they're getting filtered out by processes that can't measure what actually matters for engineering success.
Until you fundamentally rethink how you evaluate software engineering talent—moving beyond resumes, experience requirements, and algorithmic interviews toward methods that assess real engineering capabilities—you'll keep missing the great engineers who are right in front of you.
The solution isn't finding more engineers. It's building hiring processes that can actually recognize great engineering talent when it applies.