Candidate Name:
Technical Role:
Tech Stack:
Interview Round:
Technical Assessment Design
Work with the engineering manager to list must-have and nice-to-have technical skills. Categorize them by proficiency level expected: foundational, intermediate, or expert.
Choose from coding exercises, system design discussions, whiteboard sessions, or take-home assignments based on the skill being evaluated and the seniority of the role.
Ensure junior-level candidates receive problems that test fundamentals while senior candidates face architectural and scalability challenges. Mismatched difficulty wastes time and frustrates candidates.
Set up the IDE, online coding tool, or whiteboard in advance. Test that all dependencies, compilers, and access credentials work before the candidate arrives.
Define what constitutes a passing, strong, and exceptional solution for each problem. Include criteria for code quality, efficiency, communication, and edge-case handling.
Problem Selection and Preparation
Select coding or design problems drawn from actual work the team does rather than abstract puzzles. This improves predictive validity and gives candidates a realistic preview of the role.
Avoid problems with a single trick or insight. Good technical problems allow candidates to demonstrate their thinking process through different approaches, each with trade-offs.
Pre-plan two or three progressive hints for each problem. Knowing when and how to offer hints ensures a consistent candidate experience and reveals how well candidates use guidance.
Search online for your exact problem statements to ensure they are not widely published on interview prep sites. Rotate problems regularly to maintain assessment integrity.
Conducting the Technical Interview
Tell the candidate how much time they have, whether they can use documentation, and what language or tools are available. Reducing ambiguity lets candidates focus on demonstrating their skills.
Pay attention to how the candidate breaks down the problem, considers edge cases, and communicates their reasoning. Process quality is often more predictive than whether they reach the optimal solution.
When a candidate makes a design choice, ask why they chose it over alternatives. Questions like 'What are the trade-offs here?' reveal conceptual understanding beyond surface-level implementation.
Document how well the candidate explains their thought process, responds to suggestions, and handles uncertainty. Technical communication is essential for team-based engineering work.
If the interview covers multiple topics, stick to the planned time blocks. Do not let one section consume the entire session, leaving other competencies unassessed.
Code Review and System Design Evaluation
Check whether the solution handles null inputs, boundary conditions, and error states. A correct but brittle solution indicates gaps in production-readiness thinking.
Look at naming conventions, function decomposition, and comments. Code that teammates can easily understand and modify is more valuable than clever one-liners.
For senior roles, evaluate whether the candidate considers load balancing, caching, database indexing, and failure modes. Ask how the design would change at 10x and 100x scale.
Observe whether the candidate proactively writes test cases, uses print debugging, or walks through code mentally. A disciplined testing approach signals engineering maturity.
Scoring and Feedback Submission
Rate each technical competency using the predefined rubric and cite specific moments from the interview as supporting evidence. Vague feedback like 'seemed smart' is not actionable.
Score technical depth and communication effectiveness on separate dimensions. A candidate may be technically brilliant but struggle to articulate ideas, or vice versa.
If your organization maps interview performance to job levels, indicate whether the candidate's demonstrated skills align with the target level, one below, or one above.
Enter all scores and notes into the evaluation system independently to prevent anchoring bias. Read other interviewers' feedback only after you have committed your own assessment.
A technical interview checklist helps the recruitment team by providing them with a tool that makes it easier for them to assess the technical skills, problem-solving abilities and domain expertise of the candidate. The checklist gives a standardized approach that will help them assess their problem-solving skills and technical skills in the particular field of work.
There is no standardized technical interview; hence, there will always be variations when it comes to the quality of these interviews. The checklist will allow interviewers to stick to important issues that potential employees should know while avoiding trivial or subjective aspects about the job and subject matter as well as streamlines preparation time for interviewers while maintaining the rigor needed to identify top technical talent.
This checklist includes issues related to skills-mapping against the job description, coding test/assessment creation, systems design question creation, and knowledge of domain assessment criteria. This list also covers issues related to conducting the live coding session, whiteboard tests and take-home assessments, and assessing the candidate's technical communication abilities. Additional sections cover tool and environment setup, time management, and candidate experience considerations.
Personalize the checklist by choosing the technical categories, programming languages, and proficiency levels suited to your open position. Change the view from Brief to Detailed to change the list into a more thorough checklist, complete with examples of questions you could ask and a scale for evaluating responses. Share the checklist with your panel of interviewers to get everyone on the same page.
Adithyan RK is the Co-Founder and CEO of Hyring, an AI-native recruitment platform that has run over 900,000 AI interviews for companies ranging from early-stage startups to the Fortune 500. He has spent 18 years building technology businesses, starting with a digital consultancy in 2008 and a staff augmentation firm in 2017, before founding Hyring in 2022 to rebuild hiring around evidence instead of guesswork.
Expertise
Surya N is the Co-Founder and CTO of Hyring, where he architected the AI interviewing engine that has now conducted over 900,000 interviews for companies ranging from early-stage startups to the Fortune 500. A mechanical engineer who moved into artificial intelligence, he spent 6 years building AI applications inside a technology consultancy before co-founding Hyring, and wrote the first version of its AI interviewer from scratch: a system that listens, adapts its questioning in real time, and flags fraud rather than following a fixed script.
Expertise