Dedicated Frontend Development Team | React & Next.js

Feature delivery in React and Next.js -- App Router with React Server Components for pages that benefit from server-side rendering, Client Components where interactivity requires browser state. TypeScript throughout: strict mode enabled, no implicit any, discriminated unions for API response types rather than optional fields that require null-checks at every call site. State management matched to complexity: React Query (TanStack Query v5) for server state with stale-while-revalidate caching and optimistic updates, Zustand for simple global client state, React context reserved for low-frequency updates (theme, auth) rather than high-frequency data that triggers unnecessary re-renders. Server Actions for form mutations where a full API endpoint is unnecessary: POST → server-side validation with Zod → database write → revalidatePath for cache busting in a single function without a separate API layer. Tailwind CSS with consistent design token usage rather than ad-hoc values that diverge from the design system -- eslint-plugin-tailwindcss configured to catch unsorted class names and non-token values in CI. Bundle optimisation from the start: dynamic imports for heavy components (rich text editors, chart libraries, date pickers), route-level code splitting, next/image with correct sizes props so images don't request unnecessary resolution on mobile. Performance budgets enforced via Vercel build output analytics on every PR rather than investigated post-launch.

Figma-to-production component implementation with Storybook 8 for isolated development, visual documentation, and interactive design review. Component API design that covers all states: default, hover, focus, disabled, loading, error, and empty -- each documented in Storybook stories with controls so QA and design can review states and edge cases without running the full application. Radix UI Primitives or shadcn/ui for accessible, unstyled component foundations (modals, dropdowns, tooltips, comboboxes, command menus) that handle keyboard navigation, focus trapping, and ARIA roles correctly without reinventing browser accessibility patterns that are notoriously difficult to get right. Design tokens defined as CSS custom properties in a token file, mapped to Tailwind CSS v4 @theme config: changing a brand colour or spacing unit cascades through the entire codebase in one commit rather than requiring grep-and-replace across hundreds of files. Figma Variables to CSS token sync using Style Dictionary or the Figma Tokens plugin to keep the token file in sync with the design source of truth without manual translation work. Variant management with cva (class-variance-authority) so component APIs are typed and controlled -- button variants (primary, secondary, ghost, destructive), card variants (elevated, outlined, flat), and input variants (default, error, success) with TypeScript intellisense rather than free-form className strings that drift. Component testing with React Testing Library: behaviour-driven tests that survive visual refactors because they assert on user-visible outcomes, not rendered CSS.

Internationalisation (i18n) implementation when required: next-intl or react-i18next for message loading per locale, locale detection from Accept-Language header and stored user preference, RTL (right-to-left) layout support for Arabic and Hebrew locales using CSS logical properties (padding-inline-start instead of padding-left) so components don't require per-locale stylesheet overrides. Pluralisation rules, number formatting (currency symbols, decimal separators by locale), and date formatting (DD/MM/YYYY vs. MM/DD/YYYY vs. ISO 8601) handled via the Intl API rather than manual string manipulation.

SEO-relevant implementation for Next.js pages: generateMetadata functions producing unique <title>, <meta name="description">, OpenGraph (og:title, og:description, og:image, og:url), and Twitter Card tags per route. Canonical URLs to prevent duplicate content from trailing slashes or query parameters. Structured data (application/ld+json) for content types that benefit from rich search results. next/image with correct width, height, alt, and sizes props on every image so LCP images load at the correct resolution and CLS is eliminated. These are not post-launch optimisations -- they are part of the implementation specification for every page built.

Performance work tied to measurable outcomes: LCP (Largest Contentful Paint) under 2.5 seconds, CLS (Cumulative Layout Shift) under 0.1, INP (Interaction to Next Paint) under 200ms -- the metrics Google uses as ranking signals and that directly correlate with conversion rate. LCP root causes diagnosed by category: hero images loading without fetchpriority="high" or the next/image priority prop; server-rendered pages blocked by slow sequential data fetching (parallel Promise.all for independent data sources, not awaited in series); web fonts causing FOUT (flash of unstyled text) resolved with font-display: swap and preloaded <link> tags. CLS root causes: images without explicit width/height attributes causing reflow when they load; dynamic content (banners, cookie consent) injected above existing content without reserved layout space; skeleton loaders that match the final layout dimensions so content slots are pre-allocated. INP root causes: synchronous third-party scripts blocking the main thread (deferred loading via Partytown or script defer); event handlers executing too much work before yielding (breaking long tasks with setTimeout or scheduler.yield); large React component trees re-rendering from high-frequency state updates (useDeferredValue, React.memo with correct equality functions). Lighthouse CI (LHCI) integrated into GitHub Actions fails the build when performance scores drop below configured thresholds. @next/bundle-analyzer run on every dependency addition to catch size regressions before they reach production.

End-to-end test coverage with Playwright: user journeys from authentication through checkout, onboarding, and key business workflows, written with the Page Object Model (POM) pattern so a selector change in one file propagates to all tests that use that page. data-testid selectors used consistently so tests survive visual redesigns and CSS refactors without breaking. Vitest for unit and component tests: fast, TypeScript-native, compatible with React Testing Library for behaviour-driven component assertions that test user outcomes rather than implementation details. Visual regression testing with Chromatic (Storybook-integrated) or Playwright toHaveScreenshot(): catches unintended visual changes across component stories and full pages when shared components are refactored -- particularly valuable in codebases where a primitive is used in forty different contexts and a small change has broad visual effects. Accessibility compliance integrated into the development workflow rather than audited post-launch: @axe-core/playwright runs WCAG 2.1 AA checks on every Playwright test run, failing the CI build on new violations; Storybook @storybook/addon-a11y surfaces colour contrast, missing labels, and role issues at the component level before they reach integration. Manual keyboard navigation testing for complex interactive components (data tables, date range pickers, comboboxes, multi-step modals) because automated axe passes do not guarantee usable keyboard flow. ARIA roles, labels, live regions, and landmark elements implemented correctly for screen reader compatibility -- including aria-live="polite" for dynamic content updates and aria-describedby for form field error messages.

Error boundary strategy: React Error Boundaries at route level (catching rendering errors in page components without crashing the entire app), at widget level for non-critical UI sections (a broken recommendation widget should not break the page it sits on), and explicit error UI components with user-friendly messaging and a retry action. Sentry or Datadog RUM integration for client-side error tracking: source maps uploaded on every deployment so minified stack traces resolve to the original TypeScript line numbers; user context (user ID, account type) attached to error events so high-impact users' errors are prioritised in the error queue.