Solutions / Technical Hiring
Evaluate the Whole Engineer
Coding tests tell you if someone can write code. They don't tell you if they can solve ambiguous problems, design scalable systems, communicate technical trade-offs, or collaborate with a team. LayersRank evaluates the complete picture.
The limitations of code-only evaluation
The standard technical hiring process has a blind spot the size of a barn.
You put candidates through coding challenges. LeetCode-style algorithm puzzles. Timed exercises where they implement binary search trees or optimize string matching. Maybe a take-home project. Maybe a live coding session where they build something while you watch.
What does this tell you? It tells you whether someone can write code that compiles and passes test cases under time pressure. That's a real skill. It's not nothing.
But it misses most of what makes engineers valuable.
Problem Decomposition
Coding tests give clear specifications.
Real engineering work rarely does. Can they take a vague requirement and break it into tractable sub-problems?
System Thinking
Coding tests are isolated exercises.
Real systems have dependencies, failure modes, and operational concerns. Can they reason about how components interact at scale?
Communication
Coding tests are silent evaluation.
Real engineering is collaborative. Can they explain their approach to someone who doesn't share their context?
Trade-off Reasoning
Coding tests have optimal solutions.
Real engineering has trade-offs. Can they articulate why one approach is better than another given specific constraints?
Collaboration Signals
Coding tests are individual exercises.
Real engineering is team sport. Can they incorporate feedback, navigate disagreement, and help others succeed?
The result:
You hire people who are excellent at coding challenges but struggle when the problems aren't clearly specified and the solutions aren't in a textbook. We've all worked with that engineer. Brilliant at algorithms. Terrible at figuring out what to actually build. Writes elegant code that solves the wrong problem. Can't explain their work to product managers. Gets defensive when anyone questions their approach.
They probably aced every coding test you threw at them.
What LayersRank evaluates
Three dimensions, using question types that reveal different signals.
Technical Dimension
Can they do the job?
System Design
"Walk through how you'd design a notification service handling 10 million daily users. Consider different notification types, delivery guarantees, and scale requirements."
Whether candidates can think architecturally. Do they clarify requirements? Consider scale? Identify trade-offs? Address failure modes?
Debugging & Troubleshooting
"You receive an alert that API response times have increased 3x in the last hour, but error rates remain normal. Describe your diagnostic process."
Whether candidates have systematic problem-solving approaches. Do they have a methodology or thrash randomly? Consider multiple hypotheses?
Technical Trade-offs
"When would you choose eventual consistency over strong consistency? Describe a specific situation where each approach would be appropriate."
Depth of understanding. Anyone can recite CAP theorem. Fewer can apply it to specific scenarios with nuanced reasoning.
Behavioral Dimension
Can they work with others?
Collaboration
"Tell me about a time you had to work closely with a product manager or designer who had different priorities than you. How did you navigate that?"
Whether candidates can function in cross-functional environments. Did they actually influence outcomes or just complain about being overruled?
Technical Communication
"Explain a complex technical concept from your work to me as if I were a non-technical stakeholder who needs to make a decision based on it."
Whether candidates can translate between technical and non-technical contexts. Engineers who can only talk to other engineers have limited impact.
Feedback & Growth
"Tell me about a time you received critical feedback on your technical approach. What happened and how did you respond?"
Self-awareness and learning orientation. Defensive responses indicate someone difficult to work with. Thoughtful responses indicate coachability.
Contextual Dimension
Do they fit this role?
Role Understanding
"Based on what you know about this role, what do you think will be the biggest technical challenges in the first six months?"
Whether candidates have genuinely thought about the specific opportunity or are just looking for any engineering job.
Motivation Clarity
"What specifically attracted you to this role versus other opportunities you're considering?"
Commitment signals. Generic answers ("exciting technology") score lower than specific answers demonstrating understanding of what makes this role distinctive.
Career Trajectory
"Where do you see your engineering career in 3-5 years, and how does this role fit into that?"
Alignment between candidate aspirations and what the role actually offers. Misalignment predicts attrition.
Sample Questions
Engineering question examples
Real questions from our engineering assessment library, organized by role.
Backend Engineer (Senior)
Video — System Design
Difficulty: 8/10"Design a rate limiting service for an API handling 100,000 requests per second. Discuss your approach to storage, trade-offs you'd consider, and how you'd handle distributed deployment across multiple regions."
Evaluates: Architectural thinking, scale reasoning, distributed systems understanding, trade-off articulation.
Text — Technical Depth
Difficulty: 7/10"Explain the difference between optimistic and pessimistic locking. Describe a scenario where each would be the better choice, and explain why."
Evaluates: Conceptual understanding, practical application, ability to explain clearly.
Video — Behavioral
Difficulty: 6/10"Tell me about a time you had to push back on a technical decision made by someone more senior than you. What was the situation, how did you handle it, and what was the outcome?"
Evaluates: Professional courage, communication approach, influencing skills.
Frontend Engineer (Mid-Level)
Video — Technical Approach
Difficulty: 6/10"Walk me through your process for optimizing the performance of a React application that's rendering slowly. What would you check first, and how would you prioritize improvements?"
Evaluates: Performance awareness, debugging methodology, prioritization thinking.
Text — Technical Communication
Difficulty: 5/10"Explain the concept of the virtual DOM to someone who understands HTML but not React. Why does it exist, and what problem does it solve?"
Evaluates: Ability to explain concepts simply, understanding depth beyond syntax.
Video — Collaboration
Difficulty: 6/10"Describe a time when you received designs from a designer that you felt would be difficult to implement well. How did you handle that conversation?"
Evaluates: Cross-functional collaboration, communication skills, problem-solving approach.
DevOps / SRE (Senior)
Video — Incident Response
Difficulty: 8/10"It's 3am and you get paged for a P1 production incident. Walk me through your first 30 minutes: what you check, who you involve, how you communicate, and how you decide when to escalate."
Evaluates: Operational maturity, systematic approach, communication under pressure.
Text — Infrastructure Design
Difficulty: 7/10"Describe your approach to designing a CI/CD pipeline for a microservices application with 20 services. What stages would you include, and how would you handle dependencies between services?"
Evaluates: Pipeline thinking, microservices understanding, practical experience depth.
MCQ — Knowledge Validation
Difficulty: 5/10"A Kubernetes pod is stuck in 'ImagePullBackOff' state. Which of the following is the most likely cause?"
Evaluates: Baseline operational knowledge.
How technical teams use LayersRank
Replacing Phone Screens
The traditional first-round phone screen is a 30-45 minute call where an engineer asks a few technical questions and forms an impression. The problems: engineer time is expensive, impressions are inconsistent, the sample of candidate capability is tiny, and good candidates sometimes have bad calls.
LayersRank replaces phone screens with structured assessment. The candidate completes a 35-45 minute interview covering more ground than any phone screen could. Multiple question types reveal different signals. Evaluation is consistent. Engineer time shifts from conducting screens to reviewing reports.
70-80% reduction in first-round interviewer hours
Informing Technical Deep-Dives
When candidates advance to technical deep-dives, the interviewer knows exactly what to probe. The LayersRank report identifies specific strengths and concerns. “Strong system design thinking but limited examples of operational experience.” The deep-dive can focus on operational scenarios rather than re-validating system design.
This makes deep-dives more efficient and more decisive. You're not starting from scratch — you're building on known information.
Calibrating Hiring Managers
Different engineering managers have different bars. What one manager considers “strong technical” another considers “acceptable but not impressive.” LayersRank provides a consistent baseline. When every candidate has a standardized first-round score, managers can compare their own assessments against the AI evaluation.
Significant divergence prompts calibration conversations. Over time, this creates more consistent hiring standards across teams.
Technical hiring: without vs. with LayersRank
Without LayersRank
1. Candidate applies
2. Recruiter does basic screen (10 min, minimal signal)
3. Engineer conducts phone screen (45 min, inconsistent questions)
4. Coding test (2-4 hrs candidate time, narrow skill)
5. Technical deep-dive (1-2 hrs, re-asks some phone screen questions)
6. System design interview (1 hr, finally asks what should have been asked earlier)
7. Behavioral/culture interview (1 hr)
8. Hiring committee reviews (often re-debates earlier conclusions)
With LayersRank
1. Candidate applies
2. Recruiter does basic screen (10 min)
3. Candidate completes LayersRank interview (40 min, technical + behavioral + contextual)
4. Recruiter reviews scored report (15 min, advance/decline decision)
5. Focused technical deep-dive (1 hr, probing specific concerns from report)
6. Team fit conversation (45 min, chemistry and final validation)
The difference isn't subtle. It's a fundamentally different process.
Addressing engineer skepticism
Engineers are often skeptical of AI-assisted evaluation. Here's how to address common concerns.
"AI can't evaluate technical skills like a human can."
AI evaluates differently, not worse. A human engineer in a 30-minute phone screen samples a tiny slice of candidate capability and forms an impression influenced by mood, fatigue, and similarity bias. LayersRank evaluates a broader range of competencies with consistent criteria. It doesn't get tired. It doesn't favor candidates who remind it of itself. The human deep-dive still happens — just after a more rigorous first filter.
"You can't evaluate coding ability without seeing code."
You can evaluate reasoning about code without watching someone type. When candidates explain their approach to system design, debugging, or technical trade-offs, they reveal how they think. That thinking is often more predictive than whether they can implement binary search under time pressure. If you need to validate code writing, pair LayersRank with a coding exercise — but understand that coding tests evaluate a narrow skill, while LayersRank evaluates the broader capabilities that predict engineering success.
"Engineers should evaluate engineers."
Engineers should evaluate engineers — in final rounds, where human judgment about team fit, collaboration chemistry, and nuanced technical depth genuinely matters. Engineers shouldn't spend their time on repetitive first-round screens that could be structured and automated. That's not a good use of expensive engineering talent.
"What if the AI is wrong?"
Every score includes a confidence level. When confidence is high, the evaluation is reliable. When confidence is lower, you know to probe in subsequent rounds. The question isn't "is AI perfect?" It's "is AI better than inconsistent human phone screens?" The evidence suggests yes.
Frequently asked questions
Can LayersRank evaluate specialized technical skills (ML, embedded, security)?
We have question libraries for common specializations. For highly specialized roles, you can create custom questions targeting specific technical areas. The platform evaluates reasoning and communication regardless of technical domain.
How do candidates feel about this process?
Candidates generally prefer async structured assessment over phone screens. They can complete on their own schedule, they don't have to perform in real-time, and they know the evaluation is consistent across candidates. Common feedback: "I appreciated being able to think before answering" and "this felt more fair than typical phone screens."
What about candidates who communicate better verbally than in writing (or vice versa)?
Our interviews include both video and text responses, capturing both communication modes. Candidates who are stronger verbally can shine in video questions; those stronger in writing can shine in text questions. The mix also reflects real engineering work, which requires both verbal communication (meetings, presentations) and written communication (documentation, code reviews, async discussion).
How does this work for remote vs. on-site roles?
The process is identical. LayersRank is async by nature, so it works for any work arrangement. The only difference might be which questions you include — remote roles might include questions about async communication practices.
Evaluate Engineers, Not Just Code
See how LayersRank assesses the complete picture: technical depth, system thinking, communication, and collaboration. Request a demo with your actual job description.