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.

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.

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.

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.

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.