Job Description
Software Engineer II
Jasola, New Delhi
Full time
Posted 22 Days Ago
time left to apply
End Date: October 19, 2026 (30+ days left to apply)
R5389
Position: Software Engineer II, Frontend Base Location: New Delhi Location: India (Remote / Hybrid) Experience: 4+ years
About Chegg Skills
As Chegg Skills engineers, our software empowers students to move from "learning" to "earning." We build the applications and systems that help students make life-changing career transitions into high-growth job opportunities. We take pride in making education accessible to motivated career switchers, and we build the technology that helps them achieve mastery and success.
In this role, you will play a key role in a fully remote team of diverse, motivated engineers who are rethinking what education can look like. We serve thousands of students and educators every year, and your work will directly shape how those students learn and succeed.
Chegg Skills is a growing division of Chegg focused on post-collegiate learners. We are continuing to grow our engineering team to support business expansion as more students take the next step in their careers with Chegg. Join us and help scale the engineering foundation for our next phase of growth.
🚀 Role Overview
We're hiring a Software Engineer II, Frontend to own the design, quality, and delivery of features across our student- and educator-facing web applications. This role is focused on building React/Next.js product experiences, the GraphQL-powered data layers behind them, and increasingly, AI-powered learning features. You will also contribute across the stack as needed — this is a frontend-first role with full-stack reach, and you should be comfortable enough with backend concepts and AWS infrastructure to ramp into our Kotlin/Java or Python backend services when a task calls for it.
🎯 What Success Looks Like in This Role
Own frontend features end-to-end — architecture, implementation, testing, staged rollout, and production monitoring — across our student and educator web applications.
Translate product requirements into component architecture, GraphQL query/schema boundaries, and client-state contracts (React Query, Redux Toolkit, or similar) that other engineers build on.
Debug cross-system issues that surface in the UI — GraphQL supergraph errors, auth/session edge cases, server/client rendering mismatches — by tracing root cause across the stack.
Build AI-powered learning features responsibly: validate model output before it reaches the UI, design graceful fallbacks for unusable responses, and instrument these flows with telemetry.
Apply security and data-protection practices — input validation, secure auth/session handling, careful treatment of user data — as a default part of the code you ship, not a step someone else checks for.
Optimize application performance (rendering strategy, bundle size, Core Web Vitals) as an ongoing part of feature work.
Own the quality of your changes through automated tests (unit, component, and end-to-end), CI stability, and production validation.
Partner closely with Product, Design, Backend, and Content Operations to deliver and harden high-impact learner and educator workflows.
Contribute to engineering quality through strong code reviews — including review of AI-generated code — reusable patterns, shared components, and clear documentation that keeps technical debt low.
Ship end-to-end changes across the web application and its supporting APIs/schema, as needed.
Required Qualifications
Most qualified candidates will likely bring 4+ years of professional frontend engineering experience building production web applications, with demonstrated ownership of features from design through launch.
Strong hands-on experience with React and Next.js, and comfort working in TypeScript.
Working knowledge of web fundamentals — common security pitfalls (XSS, CSRF, auth/session handling), performance (rendering strategy, bundle size, Core Web Vitals), and accessibility (WCAG/ARIA basics) — and the judgment to apply them without being told to.
Experience designing and consuming APIs across common paradigms — GraphQL (schema design, codegen, querying), REST, and real-time protocols such as WebSockets — and working with at least one modern client-state approach (React Query, Redux Toolkit, or similar).
Strong testing and release-validation discipline — unit/component testing (Vitest or Jest, React Testing Library) and end-to-end testing (Playwright or Cypress).
Comfort using AI-assisted development tools responsibly, with the ability to explain, validate, and safely ship the code you produce.
Sound understanding of data structures, algorithms, and general software design principles, applied pragmatically rather than academically.
Preferred Qualifications
Experience with a CSS-in-JS styling approach and working alongside a component library (e.g., MUI).
Working knowledge of AWS infrastructure concepts (compute, storage, networking, basic service architecture) and some Node.js backend exposure — enough of a foundation to ramp into our Kotlin/Java or Python backend services when needed, even without prior production experience in those languages.
Experience with Auth0 or similar authentication providers in a Next.js application.
Experience shipping AI-powered UI — streaming responses, structured output rendering, graceful handling of model failures.
Experience contributing to shared component libraries or tooling used across multiple teams/repos.
Familiarity with frontend observability tooling (New Relic or similar).
Experience in EdTech, e-commerce, or another consumer-facing product company.
Tech Stack
Frontend: React (18/19), Next.js, TypeScript, GraphQL (Apollo tooling, codegen against a shared supergraph), React Query / Redux Toolkit / Zustand, styled-components, MUI
Backend (foundational): Node.js, AWS (compute/storage/networking basics) — enough to ramp into Kotlin/Java (Spring) or Python (FastAPI/Django) services owned by backend engineering
Testing: Vitest, React Testing Library, Playwright, MSW
Auth / Delivery: Auth0, GitLab CI
Observability: New Relic
AI / ML: OpenAI, AWS Bedrock (via shared backend integrations)
