DPDZero is a fast-growing startup building next-generation solutions in a competitive market where speed and technical excellence aren't optional—they're survival.
What they used before
Combination of online job boards and posting on subreddits.
Key Challenges
Method to evaluate specialized AI engineers is difficult, since it's a new and niche skill.
Key Outcomes
DPDZero interviewed 4 strong quality candidates in just 14 days—down from 3 months—and finally hired someone who could actually do the job.
What They Were Doing Before
The process was:
Post the role "everywhere"
Screen 100+ resumes manually
Phone screen 30 "looks good on paper" candidates
Technical interview 10-15 per week
Watch them fail basic technical questions
Repeat for 2-3 months
Eventually settle for "good enough" or start over
It wasn't working. But, it was just... the only option they knew.
The Challenges & Pain Points
DPDZero's hiring came down to 2 key problems:
1. Specialized Skills Are Impossible to Assess from Resumes
When you're hiring for AI engineers, DevOps engineers, and Data engineers, resumes lie. Someone can list "Kubernetes, Docker, Terraform, CI/CD" on their CV, but that tells you nothing about whether they can actually architect a scalable deployment pipeline or debug a failing cluster at 2 AM.
2. Interviewing Unqualified Candidates Destroyed Team Productivity
The technical team was spending ~15-20 hours per week interviewing candidates, that's time not spent shipping product, fixing bugs, or scaling infrastructure.
How Utkrusht Helped
DPDZero's entire hiring approach shifted when they used Utkrusht’s skill assessment platform.
1. Real Technical Validation, Not Resume Screening
Utkrusht's assessments don't test trivia. They don't ask "What's the difference between TCP and UDP?" They evaluate how candidates think, problem-solve, and execute under real-world conditions.
2. Specialized for Hard-to-Fill Roles
Utkrusht's assessments are also designed specifically for niche roles that actually matter to startups and SMEs building technical products: DevOps, AI engineering, Data engineering, Backend engineering, etc.
The questions aren't generic. The scenarios aren't basic. The bar is high—because that's what DPDZero needed.
"The difference was night and day. We weren't gambling on whether someone could actually do the work anymore. The assessments had already answered that question. We just needed to make sure they'd fit with the team—and they did."
The Results
The transformation wasn't just about speed—though going from 2-3 months to 14 days is pretty damn good. It was about finally being able to hire people who could actually do the job.
Time to Hire: 14 Days (vs. 2-3 Months)
That's ~80% faster than their previous timeline. Every week saved is a week of productive work instead of desperate searching.
Candidate Quality: 4 Strong Candidates (vs. 60+ Weak Ones)
With Utkrusht, they interviewed 4 candidates total—and all 3 were technically qualified. That's a 95% reduction in wasted interview time.
Hire Quality: Someone Who Actually Delivers
The candidate has been performing well for months. No post-hire regret. No "we thought he could do it, but..." conversations. He showed up, did the work, and proved the assessments weren't lying.
That's the real ROI: confidence that your hire will work out.
What Stood Out Most
The method to assess candidates is 10x better than all the tools out there who simply conduct MCQ quizzes and test theory knowledge..
Assessment-First Hiring Changes Everything
Most hiring is backwards. You screen resumes, do phone calls, bring people in for interviews, and then—if you're lucky—you find out in the technical round whether they can actually do the work.
By that point, you've invested hours. You've gotten excited about a candidate. You're hoping they'll pass because you don't want to start over.
Utkrusht flips the script: prove you can do the work first, then we'll talk.
Why This Matters for Specialized Roles
When you're hiring for generic roles—customer support, sales, operations—you can get away with resume-first hiring. The skills are transferable. The learning curve is manageable. A bad hire is fixable.
But when you're hiring for tech skills, especially niche ones like AI engineers, DevOps engineers, and Data engineers, you can't afford to guess. These roles are:
Too specialized: The skills aren't common. You can't just "train someone up."
Too new: AI engineering barely existed 3 years ago. Everyone's resume is a fiction.
Too critical: A bad DevOps hire means infrastructure fires. A bad AI hire means your ML systems don't work.
For these roles, assessment-first hiring isn't a nice-to-have—it's the only thing that actually works.
Why DPDZero Chose Utkrusht Over Others
DPDZero had options. They could've kept using traditional recruiters. They could've tried other assessment platforms. They could've built their own technical tests.
So why Utkrusht?
1. Built for Specialized Technical Roles
Most platforms are designed for "software engineer" hiring at scale—think Big Tech screening thousands of candidates for generic roles.
Utkrusht is built for startups and SMEs hiring specialized, hard-to-fill technical roles. The assessments aren't generic LeetCode problems. They're designed specifically for DevOps, AI engineering, Data engineering, and other roles where depth matters more than breadth.
2. Built for Small Engineering Teams
Not for big companies with big budgets. Not for companies with several different skills. Utkrusht's platform is built specifically for small engineering teams who don't have much resources to assess technical skills of candidates.
"We finally found someone who could actually do the job perfectly.. Not someone who interviewed well. Not someone with an impressive resume. Someone who'd proven they could execute—and then he did exactly that. That's what we'd been missing for months."
What's Next
For roles where technical depth is non-negotiable, skills-first hiring isn't just faster—it's the only approach that actually works.
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