The questions frontend developers actually get asked — with STAR-structured sample answers you can rewrite in your voice. Practice the rooms before you're in them.
Profile first with the React DevTools profiler and the browser performance panel — don't guess. Look for unnecessary re-renders (memoize with React.memo/useMemo where the profiler proves a cost), oversized bundles (code-split routes, lazy-load), and layout thrash. I cut an LCP from 4.1s to 1.3s mostly via route-level splitting and an image pipeline, not micro-optimizations.
Semantic HTML first — a real button, not a div with onClick. Then keyboard operability, focus management, ARIA only where semantics fall short, sufficient contrast, and testing with a screen reader plus automated axe checks in CI. I took a checkout flow to WCAG 2.1 AA, which cleared an enterprise compliance blocker.
I match the tool to the scope: local state for component concerns, server-cache libraries (React Query/SWR) for server state, and a light global store (Zustand/Context) only for truly shared client state. The common mistake is putting server data in a global store and hand-syncing it — I let a cache library own that.
LCP (largest paint), CLS (layout shift), and INP (interaction responsiveness). LCP: prioritize the hero, optimize images, reduce render-blocking JS. CLS: reserve space for images/embeds and avoid late-injected content. INP: break up long tasks and defer non-critical work. I track them in the field with web-vitals, not just lab Lighthouse.
S: A launch needed a feature in days; the clean solution needed a shared abstraction we didn't have. T: Ship without creating long-term debt. A: I shipped a contained, well-tested local version and filed the refactor with a clear boundary so it wouldn't leak. R: We hit the launch, and the refactor landed two sprints later without a rewrite.
Mobile-first responsive CSS, a tested set of real target browsers/devices, visual-regression and Playwright tests in CI, and progressive enhancement so core flows work without the latest APIs. I set up a testing pyramid that dropped per-release UI regressions from ~6 to under 1.
Types catch a whole class of errors at edit-time, make refactors safe, and document intent for the next developer. The cost is some upfront friction. On a 120-screen migration to hooks + TypeScript, the types eliminated stale-state and prop-shape bugs that had been recurring in production.
Early and in their tool — I review designs for feasibility and edge/empty/error states before they're 'final', build to a shared design system so spacing and tokens match, and flag where a small design change saves significant engineering. A shared component library is what makes that partnership fast.
Every strong behavioral answer follows the same four-part structure: Situation(the context — 2 sentences), Task (what success looked like — 1 sentence),Action (what you actually did, 3-5 specific steps), and Result(the measurable outcome). Most candidates over-invest in Situation and under-invest in Result. The Result is where the interviewer scores you.
Voice or text. Per-answer STAR scoring. Saved across devices.
Start freeThe ApplyVita Career Team builds the resume-scoring and job-matching tools at the core of ApplyVita. Our guidance is grounded in the same four-component ATS rubric our product scores resumes on — content and impact, keyword match, formatting, and skills — and in current recruiter and hiring-manager practice. Every guide is checked against that rubric before it is published, and updated as hiring norms change.