Frontend Engineer

Middle–Senior Frontend Engineer (React/Next.js) with strong JavaScript (ES6+), experience integrating AI APIs (OpenAI/Claude), and solid understanding of prompt engineering and LLM limitations. Must be skilled in building AI-powered UIs (chat, assistants, generators), handling real-time/streaming data, and ensuring performance, scalability, and UX quality. Should be familiar with AI coding tools and agent-like workflows, and comfortable working with modern frontend stacks (Node.js, Vercel, or similar is a plus).

1. How does React handle state updates and re-rendering, and how can you optimize performance in a Next.js app?
   React batches state updates and triggers re-renders based on changes in state or props. Performance can be optimized using memoization (React.memo, useMemo), code splitting, and server-side rendering features in Next.js.

2. What are the key differences between CSR, SSR, and ISR in Next.js?
   CSR renders on the client, SSR renders on each request, and ISR allows static generation with periodic revalidation. ISR is useful for balancing performance and freshness of data.

3. How would you implement a real-time streaming UI for AI responses in React?
   You can use ReadableStream, WebSockets, or Server-Sent Events (SSE) to progressively update the UI. Managing partial state updates ensures smooth streaming UX.

4. What challenges arise when integrating AI APIs like OpenAI, and how do you handle them?
   Challenges include rate limits, latency, and failures. These can be handled with retries, exponential backoff, caching, and graceful fallbacks in the UI.

5. Explain prompt engineering and how it impacts frontend AI features.
   Prompt engineering involves structuring inputs to guide LLM outputs. On the frontend, this ensures consistent responses, better UX, and reduced ambiguity in AI-generated content.

6. How do you manage error handling and fallback strategies in AI-powered UIs?
   Use try/catch, timeout handling, and UI fallbacks such as skeleton loaders or cached responses. Provide user feedback and retry options when failures occur.

7. What techniques would you use to ensure accessibility in a React-based AI chat interface?
   Use semantic HTML, ARIA roles, keyboard navigation, and screen reader support. Ensure dynamic updates (like streaming messages) are announced properly.

8. How can you optimize large-scale React applications for scalability?
   Use component modularization, lazy loading, proper state management (e.g., Zustand, Redux), and efficient API handling. Also apply caching and CDN strategies.

9. What are agent-like workflows in AI development, and how would you integrate them into a frontend product?
   Agent workflows involve chaining AI tasks (planning, execution, validation). On the frontend, they can orchestrate multi-step user interactions like automated data extraction or generation flows.

10. How do AI coding tools like Cursor or Codex improve frontend development productivity?
    They accelerate code generation, refactoring, and debugging. Developers can use them to scaffold components, write boilerplate, and experiment faster with AI-driven features.

Infatica.io, a global provider of proxy and DaaS solutions, is building a high-load web scraping platform and is looking for a Frontend Engineer to shape its next-generation UI. You’ll develop scalable React (Next.js) interfaces, integrate AI APIs (OpenAI, Claude), and build real-time, AI-powered experiences like chat and assistants using modern JavaScript (ES6+). The role is fully remote, offers competitive compensation, and gives you strong ownership over architecture and product decisions. Join to work at the intersection of AI and web scraping, influence core product development, and grow with a fast-moving, innovation-driven team.