Evaluate React Developer candidates across 4 weighted areas: technical proficiency, systems and trade-offs, evidence and rigour, and collaboration and communication. Technical proficiency leads at 35%, so probe hooks depth: useMemo versus useCallback, dependency arrays, custom hooks, Suspense, and how they type props and generics in TypeScript with React 18 concurrent rendering. Use the rubric to compare role-specific evidence consistently.
For technical proficiency, look for evidence the candidate explains re-render causes precisely, names memoisation pitfalls, writes typed custom hooks, and distinguishes server from client components confidently. For systems and trade-offs, look for evidence the candidate justifies state and routing choices against real constraints, cites bundle or Lighthouse numbers, and admits where the trade-off later hurt.
Apply the written 1–5 anchors to every answer, record the evidence behind each rating, and use the factor weights to reach a consistent overall assessment.
Complete evaluation framework
What to assess and how to score it
Review the evidence signals before interviewing. Then use the anchored descriptions—not instinct alone—to choose the score that best matches each answer.
01
Evaluation factor
Technical proficiency
35% weight
Probe hooks depth: useMemo versus useCallback, dependency arrays, custom hooks, Suspense, and how they type props and generics in TypeScript with React 18 concurrent rendering.
Evidence to listen for
Command of the languages, frameworks, and data tools the role actually uses
Understands correctness, performance, and failure modes, not just syntax
Has opinions on testing and can justify them
Reads and reasons about code they did not write
Five-point scoring guide
1
Poor
Cannot work independently; fundamentals are missing.
2
Needs Improvement
Weak fundamentals; output needs heavy review.
3
Satisfactory
Competent for the role; needs guidance on complex or unfamiliar work.
4
Very Good
Strong practitioner; handles hard problems with little guidance.
5
Excellent
Explains re-render causes precisely, names memoisation pitfalls, writes typed custom hooks, and distinguishes server from client components confidently.
02
Evaluation factor
Systems and trade-offs
25% weight
Ask how they chose state tools: Redux Toolkit, Zustand, TanStack Query, or Context, plus bundle size, code splitting, and Next.js versus Vite decisions.
Evidence to listen for
Reasons about scale, latency, cost, and failure before writing code
Names the trade-off they chose and what they gave up
Understands the data lifecycle end to end
Anticipates what breaks at ten times the volume
Five-point scoring guide
1
Poor
No thinking beyond the immediate task; no awareness of scale or failure.
2
Needs Improvement
Limited architectural awareness; struggles with design decisions.
3
Satisfactory
Works within an existing design; makes sound local decisions.
4
Very Good
Designs for scale and maintainability; articulates trade-offs clearly.
5
Excellent
Justifies state and routing choices against real constraints, cites bundle or Lighthouse numbers, and admits where the trade-off later hurt.
03
Evaluation factor
Evidence and rigour
25% weight
Check testing and performance evidence: React Testing Library, Playwright, React Profiler traces, Core Web Vitals like LCP and INP, accessibility audits with axe.
Evidence to listen for
Validates results rather than trusting output
Knows how their work is measured and what a bad result looks like
Can describe a time their own analysis or model was wrong and how they caught it
Careful about data quality, leakage, and silent failure
Five-point scoring guide
1
Poor
Ships unvalidated work; no notion of how correctness is checked.
2
Needs Improvement
Validates superficially; misses obvious quality or leakage issues.
3
Satisfactory
Reasonable checks in place; rigour drops under time pressure.
4
Very Good
Validates thoroughly; can name a real error they caught in their own work.
5
Excellent
Cites measured before and after figures on render time or LCP, and describes tests that caught actual regressions in production.
04
Evaluation factor
Collaboration and communication
15% weight
Assess how they work with designers and backend: Figma handoff, component library or Storybook ownership, API contract disputes, and code review habits on pull requests.
Evidence to listen for
Explains technical work to non-technical stakeholders
Gives and takes code or peer review constructively
Documents enough that the work survives their absence
Aligns with team process rather than working around it
Five-point scoring guide
1
Poor
Cannot work in a team; resistant to feedback.
2
Needs Improvement
Communication issues create rework; lone-wolf tendencies.
3
Satisfactory
Adequate team member; documentation and review participation are light.
4
Very Good
Communicates well; reliable reviewer and collaborator.
5
Excellent
Describes concrete handoff friction resolved, maintained a shared component library, and gives review feedback others acted on.
Evidence-led prompts
Interview questions for a React Developer
Use these prompts to surface evidence for the weighted factors above and compare candidates against the same role-specific criteria.
01
Tell me about your hands-on experience as a React developer.
02
Can you explain a complex problem you faced in a React project and how you solved it?
03
What specific features of React have you worked with?
04
Can you explain how you manage state in React?
05
How do you structure your React projects, and why?
