Frontend Developer (Founding team)

You will own the entire front-end experience of Exterview, building the interface that powers the next generation of AI-led hiring intelligence.
This goes beyond writing React or Next.js code you’ll be crafting the Human + AI collaboration layer that merges recruiter workflows, AI insights, and live interviews into a unified, frictionless experience.

Every interaction from candidate evaluation to interviewer feedback and AI report visualization should feel fluid, intelligent, and purposeful.
You’ll work closely with Product, AI, Backend, Prompt Engineering, and QA teams to ensure that AI-driven screening, voice/avatar interviews, and hybrid assessments translate into a performant, elegant, and enterprise-grade UX.

Your daily execution stack will revolve around Linear, Notion, and GitHub, with real-time collaboration and design system ownership at the core of your work.

• Build a modular, typography-first design system using Tailwind CSS and shadcn/ui.

• Ensure accessibility, responsiveness, theming (dark/light), and enterprise scalability.

• Establish component guidelines and Storybook documentation for consistent implementation.

• Architect dynamic UIs for AI Voice, Video, and Avatar Interviews integrating live transcripts, sentiment visualization, and fraud detection indicators.

• Implement recruiter and interviewer dashboards for role-based access, scheduling, and candidate analytics.

• Implement WebSockets for live interviewer-candidate interactions, presence indicators, and synchronized feedback editing.

• Manage conflict resolution via OT/CRDT frameworks ensuring seamless multi-user collaboration.

• Design and implement UI for AI streaming outputs interview summaries, skill analysis, and scoring.

• Visualize AI + Human feedback fusion with diff views, accept/reject flows, and confidence scores.

• Build interfaces for real-time video analytics, voice sentiment graphs, and fraud/liveness indicators.

• Render AI reports transcripts, summaries, and skill radar charts with intuitive hierarchy and export capability.

• Own performance budgets: SSR-first pages, sub-200ms interactions, and 16ms/frame rendering targets.

• Optimize for SEO, accessibility, and enterprise-grade responsiveness across devices.

• Implement secure iframe sandboxes for mini-app modules and embedded AI tools.

• Handle sensitive data (voice, transcripts, reports) with role-based access controls and secure state isolation.

• Work with PMs to translate PRDs (Notion) → deliverables (Linear) → tracked executions (GitHub).

• Align front-end milestones with backend and AI model delivery sprints.

• Maintain clean, modular repos with TypeScript, linting, hooks, and preview deploys.

• Own Storybook or MDX documentation for components and UI workflows.

• Recruiter dashboard live with AI insights, candidate listings.

• Sub-200ms interaction latency validated through RUM metrics.

• AI Voice Interview UI with streaming transcript and summary shipped.

• Full hybrid interview workspace (multi-user, feedback sync, report generation) live.

• Palette open-to-action <50ms p95; rendering smoothness <16ms/frame.

• 70% of interview reports generated via AI-assisted workflows.

• FE regression rate <2%; 90%+ test coverage for interview and candidate modules.

• 8–10+ years of experience in frontend engineering (React + Next.js at scale).

• Deep expertise in SSR/CSR hybrids, RSC, caching, and state management.

• Proven experience building real-time collaborative UIs (WebSockets, OT/CRDT).

• Eye for enterprise-grade UX, accessibility, and design consistency.

• Prior delivery of data-heavy dashboards or AI-interactive interfaces in production.

• Experience with WebRTC, voice/video rendering, or avatar-based UIs.

• Familiarity with GraphQL, microservices, and multi-cloud deployment (AWS/Azure).

• Contributions to open-source UI frameworks (Slate, ProseMirror, Next.js).

• Startup or founding engineer experience.

• Exposure to LLM-driven applications, speech-to-text, or agentic AI flows.

• Core: Next.js (App Router), React, TypeScript, Tailwind CSS, shadcn/ui, Lucide Icons.

• Architecture: MERN + Microservices, GraphQL API Gateway, Azure AI Services, AWS Cloud.

• Realtime: Socket.IO, OT/CRDT.

• Motion: Framer Motion for micro-interactions.

• Auth: Cognito / Firebase (Google, GitHub, LinkedIn OAuth).

• AI Layer: Exterview AI Agents (Screening, Interview, Feedback, and Report Generators).

• Tooling: Linear (Execution), Notion (Specs), GitHub (Repos), Storybook (UI Docs).

Replicate the home page UI of
https://exterview.ai/

using modular React components and Tailwind CSS.

This assessment focuses purely on UI implementation, code structure, and styling fundamentals.

Evaluate the candidate’s ability to:

• Translate an existing website UI into code

• Write clean, modular React components

• Use Tailwind CSS effectively

• Maintain good folder structure and readability

Build a Next.js application that visually replicates the Exterview home page.

• Replicate the layout, sections, spacing, and typography

• Ensure the page is responsive (desktop + mobile)

• Break the page into reusable components

Examples:

• Navbar

• Hero section

• Feature sections

• Call-to-action sections

• Footer

Pixel-perfect accuracy is not required, but the structure and visual hierarchy should closely match.

• Framework: Next.js

• Language: JavaScript or TypeScript

• Styling: Tailwind CSS

• Component-based architecture (no single large file)

• No backend

• No authentication

• No animations

• No AI functionality

• No API integrations

This is a pure frontend UI task.

• GitHub repository with the source code

• README.md including:

  • Setup instructions

  • Brief explanation of component structure

• (Optional) Live deployment (Vercel preferred)

CategoryWeightComponent Structure & Modularity30%Tailwind CSS Usage & Styling30%Responsiveness20%Code Readability & Folder Structure20%
For more than 5 years people

Objective:
Validate the candidate’s ability to build a high-performance, real-time, AI-driven hiring workspace.

Challenge (PoC):
Build a Next.js application featuring:

• Candidate dashboard connected to a mock AI Screening API.

• Real-time transcript rendering from a sample voice input stream.

• Interview block editor (Question → Response → Feedback).

• Mini sandbox for AI-generated report preview.

• Command palette (Cmd+K) with fuzzy search.

• Google/GitHub login (Firebase Auth).

Performance Targets:

• Sub-200ms interaction latency.

• Palette open-to-action <50ms.

• 60fps animation in transcript visualization.

Deliverables:

• Deployed demo (Vercel preferred).

• GitHub repo with modular, documented code.

• README outlining architecture, state management, and tradeoffs.

• 5-min Loom walkthrough demo.

Evaluation Criteria:

• Architecture & Code Quality (25%)

• Real-Time UX & Performance (25%)

• AI & Interaction Layer (20%)

• UI/UX Polish & Accessibility (10%)

• Security & Sandboxing (10%)

• Tests & Documentation (10%)