Most hiring processes for engineers are broken as hell. Companies obsess over leetcode problems and algorithm trivia while missing the stuff that actually matters. I've hired 20+ engineers over the past two years at Protocoding, and let me tell you, the best performers rarely aced the whiteboard session. They're the ones who asked better questions, admitted what they didn't know, and showed they could think beyond just writing code.
Y'all are optimizing for the wrong things. The industry treats hiring like we're building NASA rockets when most of us are building CRUD apps and integrations. Don't get me wrong, technical skills matter. But if you can't communicate with clients, can't handle ambiguity, or need your hand held through every decision, you're not gonna make it at a consultancy. The resume tells you nothing about how someone handles pressure or whether they'll ghost you when things get tough.
Problem Solving Over Pattern Matching
Here's what I've learned: great engineers don't memorize solutions, they understand problems. Last month, we had a candidate who couldn't reverse a binary tree but spent 30 minutes walking me through how he'd debug a production issue. He asked about monitoring, logging, user impact, and rollback strategies. That's the person I want on my team when everything's on fire at 2 AM. The binary tree guy? He'd probably just restart the server and hope for the best.
Real problem solving shows up in how people approach unknowns. One of our best hires came from a bootcamp and had never touched our tech stack. But when I gave him a vague project description, he didn't panic or ask for step-by-step instructions. He broke it down into smaller problems, researched similar solutions, and came back with three different approaches. Compare that to senior engineers who freeze up if you don't hand them exact requirements and a detailed spec.
This matters more in consulting because every client brings different problems. You can't pattern match your way through a healthcare integration when you've only built e-commerce sites. But if you can think through systems, ask the right questions, and iterate based on feedback, you'll figure it out. The best engineers I've worked with treat every new project like a puzzle to solve, not a chore to complete.
Communication Trumps Code Skills
I'd rather hire a decent engineer who can explain complex things simply than a coding genius who can't hold a client conversation. Last year, we had a brilliant developer who wrote beautiful, efficient code but couldn't articulate technical tradeoffs to non-technical stakeholders. Every client call became this painful translation exercise where I had to interpret his mumbled explanations about database optimization. Meanwhile, another team member with half his technical chops became our go-to for client demos because he could make complex integrations sound straightforward.
Communication isn't just about client meetings though. It's how you document your code, how you explain bugs in Slack, how you give feedback during code reviews. The engineers who write clear pull request descriptions, who can explain their architectural decisions in plain English, who ask clarifying questions instead of making assumptions - those are the ones who make everyone else better. Bad communicators create technical debt in the form of confusion and misunderstandings.
- Can you explain a technical concept to your grandmother without using jargon?
- Do you write commit messages and PR descriptions that actually help reviewers understand your changes?
- When you're stuck, do you ask specific questions or just say 'it's not working'?
- Can you push back on unrealistic timelines without being defensive or dismissive?
These communication patterns show up early in the interview process. Pay attention to how candidates ask questions about the role, the company, or the technical challenges. Do they seek to understand or just check boxes? When they explain their past projects, do they focus on the business impact or just the technical implementation? The best engineers I've hired could tell me not just what they built, but why it mattered and what they'd do differently next time.
Ownership Mentality vs Task Completion
There's a huge difference between engineers who complete tasks and engineers who take ownership of outcomes. Task completers will build exactly what you specify, even if it's obviously wrong. Owners will push back, suggest alternatives, and think about edge cases you didn't consider. I learned this lesson the hard way with a contractor who spent two weeks building a feature that made no business sense because 'that's what the spec said.' An owner would have questioned the requirement on day one.
Ownership shows up in how people handle bugs and incidents too. Task completers will fix the immediate issue and move on. Owners will fix the bug, figure out why it happened, and prevent similar issues in the future. They'll update documentation, add monitoring, or refactor the problematic code. One of our engineers found a race condition that was causing intermittent failures. Instead of just patching it, he spent extra time implementing proper error handling and wrote a post-mortem that helped us catch similar issues across other projects.
This mindset is crucial in consulting because you're often working with limited oversight on client projects. I can't micromanage every decision when we have five active projects. I need people who will make good judgment calls, escalate real blockers, and deliver solutions that actually solve the business problem. The difference between good and great engineers isn't technical ability, it's this sense of responsibility for the end result.
Handling Ambiguity and Change
Consulting work is messy. Requirements change, clients don't know what they want, and half the time you're building something that's never been built before. Some engineers thrive in this environment and others completely fall apart. The ones who succeed are comfortable with ambiguity and can make progress even when they don't have perfect information. They'll build something, get feedback, iterate, and gradually converge on the right solution.
I test this during interviews by giving candidates intentionally vague project descriptions. How do they respond? Do they ask thoughtful questions to narrow the scope? Do they identify the core problem they're trying to solve? Or do they get paralyzed by the lack of detailed requirements? Last week, I described a client who 'wanted to automate their workflow' without giving specifics. The best candidate immediately started asking about current processes, pain points, and success metrics. The worst one asked me to write a detailed specification.
Change management is equally important. Clients will pivot, budgets will shift, and technical requirements will evolve. Engineers who adapt well treat these changes as new information, not personal attacks on their previous work. They'll refactor code without ego, pivot to new approaches without complaining, and help the team understand the implications of changes. The engineers who can't handle this flexibility become bottlenecks and sources of frustration for everyone involved.
“The best engineers treat every setback as data, not defeat.”
Culture Fit and Team Dynamics
Technical skills can be taught, but personality and work style are much harder to change. We're a small team working on complex projects with tight deadlines. If someone can't handle feedback, doesn't pull their weight, or creates drama, they'll poison the entire dynamic. I've seen brilliant engineers who were net negative contributors because they made everyone else's job harder through their attitude or work habits.
Culture fit doesn't mean hiring clones or avoiding diverse perspectives. It means finding people who share core values about quality, communication, and collaboration. We value directness over politeness, results over process, and learning over ego. Someone who gets defensive about code reviews, who won't admit mistakes, or who always has excuses for missed deadlines isn't going to work regardless of their technical background. These patterns show up quickly in small teams where everyone's performance affects everyone else.
I pay attention to how candidates talk about their previous teams and managers. Do they take responsibility for failures or blame external factors? When they describe conflicts, do they show empathy for other perspectives? How do they handle disagreement or feedback during the interview process itself? Red flags include badmouthing former colleagues, making excuses for every project that didn't go well, or showing impatience when asked to explain their reasoning.
What This Means for Your Hiring Process
Stop optimizing your interviews for algorithmic problem solving and start testing for the skills that actually matter. Give candidates real problems from your domain, observe how they think through ambiguity, and see how they communicate their reasoning. Have them explain past projects to non-technical team members. Ask about times they had to change direction or handle difficult feedback. These conversations will tell you way more about job performance than whether someone can implement quicksort from memory.
And remember, hiring is a two-way street. The best engineers are evaluating you just as much as you're evaluating them. They want to work on interesting problems with competent teammates and fair compensation. If your interview process is broken, you're not just missing good candidates, you're actively repelling them. Fix your hiring, and you'll start attracting the kind of engineers who actually move the needle instead of just writing code.
