The Real Cost of a Bad Engineering Hire
Everyone knows a bad hire is expensive. But when people throw around numbers, they usually just think about salary. The actual cost is so much worse.
I worked for many startups. I've seen bad engineering hires up close. Not "this person is terrible" bad. Usually it's more subtle than that. Wrong fit, wrong skill level, wrong expectations. And the damage compounds fast.
The obvious cost: salary
Let's start with the number everyone thinks about. A mid-level engineer in the US costs roughly $120K-$180K in total compensation when you include benefits, equipment, and taxes. If someone doesn't work out and leaves or gets let go after 6 months, that's $60K-$90K in direct salary costs, plus the recruiting fees you paid to find them (typically 15-25% of base salary if you used an agency).
So the direct cost of a failed 6-month hire is somewhere in the range of $80K-$130K. That's painful but it's honestly the smallest part of the problem.
The hidden cost: what they built
Here's where it gets ugly. A bad engineering hire doesn't just take up a salary slot. They write code. Code that other people have to maintain, fix, or rewrite after they leave.
I've seen entire features get thrown away after someone departed because the code was so tangled that fixing it would take longer than rebuilding from scratch. That's not just the departing engineer's time wasted. That's 2-3 other engineers spending weeks undoing the damage.
Technical debt from a bad hire can linger for years. Quick hacks that seemed fine in the moment become landmines buried in the codebase. Six months after someone leaves, a production outage traces back to a shortcut they took. The team groans. Everyone loses a weekend.
The cost nobody talks about: team morale
This one is hard to quantify but it might be the most expensive of all.
Good engineers want to work with other good engineers. When you bring someone onto the team who can't keep up, who writes sloppy code, who doesn't understand the architecture, the whole team feels it. They're doing extra code reviews. They're explaining the same concepts repeatedly. They're fixing bugs they didn't create.
After a while, your best people start thinking about leaving. Not because of the bad hire specifically, but because the environment has shifted. The pace slowed down. The code quality dropped. The energy changed. And once your best engineer starts interviewing elsewhere, you've got a much bigger problem than the original bad hire.
According to the Society for Human Resource Management, replacing a highly skilled employee can cost up to 200% of their annual salary. If your bad hire causes one good engineer to leave, you've just doubled your losses.
The roadmap cost
Every engineering team has a finite amount of work it can ship. A bad hire doesn't just contribute zero. They contribute negative. Other engineers spend time onboarding them, reviewing their code, and fixing their mistakes. The team's effective output drops.
I've seen product timelines slip by months because of this. Features that were supposed to ship in Q1 get pushed to Q3. The sales team is selling something that doesn't exist yet. Customers get frustrated. Competitors gain ground.
The compounding effect here is brutal. A 6-month hiring mistake can easily create a 3-month roadmap delay, which cascades into missed market windows, delayed revenue, and strategic setbacks that are impossible to put a dollar figure on.
The interviewing cost
People forget this one. Hiring someone means your team spent significant time interviewing them. For a typical engineering hire, you might have 4-6 people involved across phone screens, technical interviews, system design rounds, and team fit conversations. That's easily 15-20 hours of engineering time per candidate.
If you hired the wrong person, all of that time was wasted. And now you get to do it again. Another job posting, another round of resume screening, another set of interviews. Your team is spending their time evaluating candidates instead of building product. Again.
So what do you actually do about this?
The answer isn't to make the interview process longer. Adding more rounds just makes the process slower and more painful for candidates, without necessarily improving outcomes. Six interviews doesn't catch problems that four interviews missed.
The answer is better data before the interview even starts.
If you know going in that a candidate has relevant experience with your tech stack, has been at their current job for a reasonable amount of time (not a pattern of 3-month stints), has salary expectations in your range, and has demonstrable technical skills, your interviews become confirmation rather than exploration.
This is what we're building at Candyfloss. We surface the signals that predict good hires: real technical skills from GitHub activity, career trajectory patterns, salary benchmarks, job change timing. The goal is to help you walk into every interview already knowing this person is likely a fit. The interview then becomes about culture and collaboration, not basic qualification screening.
You still need good interviews. You still need to assess culture fit. But when your candidate pipeline is pre-qualified with real data, the odds of a bad hire drop significantly.
And at $80K-$130K minimum per failed hire (realistically much more when you count the hidden costs), even preventing one bad hire per quarter pays for better tooling many times over.