Lead Software Engineer

Chegg; United States; Hybrid; USD 42,000 - 84,000; Full time

Job summary

Chegg Skills is hiring a Senior Software Engineer, Backend, to own design, reliability, and scalability of backend services and APIs. You will build robust distributed systems, orchestration workflows, and backend infrastructure powering learner-facing experiences.

This is a backend-first role with some full-stack reach. You will contribute to AI-assisted backend features, collaborate with Product, Data Engineering, Platform/SRE, and Content Operations, and ship end-to-end changes across

Qualifications

• 7+ years of professional software development experience building production backend systems.
• Strong backend system design experience with distributed systems, scalability, reliability patterns, and service architecture.
• Experience with Java/Kotlin and/or Python-based backend systems (Spring, FastAPI, Django, or similar) and API design with GraphQL integration.
• Experience with workflow orchestration systems (Temporal, AWS Step Functions, Airflow, or similar).
• Experience debugging production issues end-to-end, with retries, timeouts, idempotency, and workflow/state handling.
• Strong testing and release-validation discipline; observability and on-call ownership.
• Comfort using AI-assisted development tools and contributing to AI-enabled backend features.
• Exposure to React/Next.js or frontend web apps to support full-stack changes.
• Familiarity with LLM APIs (OpenAI, Anthropic, etc.) or agentic workflow patterns.

Responsibilities

• Design and build backend services and distributed systems focused on scalability, reliability, and maintainability.
• Develop GraphQL-powered APIs and workflow-driven systems for learner-facing and operational experiences.
• Improve robustness of async/integration-heavy workflows with retries, idempotency, and error handling.
• Enhance operational readiness with dashboards, alerts, runbooks, and on-call support.

Skills

7+ years exp

Backend design

Java/Kotlin

Python

GraphQL API

Temporal workflow

Observability

AI tools

Full-stack exposure

On-call

Tools

Spring

FastAPI

Django

Temporal

AWS

Docker

Job description

Job Description - SSE Backend Engineer

Position: Lead Software Engineer, Backend

Base Location: New Delhi

Location: India (Remote / Hybrid)

Experience: 7+ 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 leading 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.

About the Role

We're hiring a Senior Software Engineer, Backend to own the design, reliability, and scalability of our backend services and APIs. This role is focused on building robust distributed systems, workflow orchestration, and backend infrastructure that powers learner-facing and operational experiences. You will also contribute to the web layer as needed this is a backend-first role with full-stack reach. What You’ll Do Design and build backend services and distributed systems with a focus on scalability, reliability, and maintainability. Build and extend GraphQL-powered APIs and workflow-driven systems that support learner facing and operational experiences. Improve reliability for integration-heavy and asynchronous workflows, including retries, idempotency, error handling, and recovery paths. Improve operational readiness through dashboards, alerts, runbooks, and hands‑on incident debugging.

Own the quality of your changes through automated tests, CI stability, rollout checks, and production validation. Work with or alongside AI/LLM-powered systems integrating APIs, contributing to agentic workflows, or extending AI-assisted backend features. Partner closely with Product, Design, Data Engineering, Platform/SRE, and Content Operations to deliver and harden high-impact workflows. Contribute to engineering quality through strong code reviews, reusable patterns, and improvements to delivery speed and system reliability. Ship end-to-end changes across backend services and web applications, including API, schema, and UI updates, as needed.

Required Qualifications

Most qualified candidates will likely bring 7+ years of professional software development experience building production backend systems. Strong backend system design experience distributed systems, scalability, reliability patterns, and service architecture. Strong experience with Java/Kotlin and/or Python-based backend systems (Spring, FastAPI, Django, or similar frameworks), plus API design and GraphQL integration. Experience with workflow orchestration systems (Temporal, AWS Step Functions, Airflow, or similar). Experience debugging production issues end to end, from symptom to root cause, fix, and prevention. Experience working on async or integration-heavy systems, including retries, timeouts, idempotency, and workflow/state handling. Strong testing and release-validation discipline in environments where engineers own quality directly. Experience with observability and operational ownership, including dashboards, alerts, runbooks, and participation in on‑call support. Comfort using AI‑assisted development tools responsibly, with the ability to explain, validate, and safely ship the code you produce. Some exposure to React/Next.js or frontend web applications sufficient to contribute to full stack changes. Preferred Qualifications Familiarity with LLM APIs (OpenAI, Anthropic, etc.) or agentic workflow patterns.

Experience with Temporal specifically for workflow orchestration. Experience with Kotlin/Java and Spring, or Python with FastAPI/Django. Experience with internal tooling or operations platforms such as Retool. Experience with analytics or experimentation instrumentation. Experience with data ingestion, backfills, or data-quality remediation

work.

Tech Stack Backend: Python (FastAPI / Django), GraphQL, Kotlin / Java, Spring-based services, Temporal Frontend: React / Next.js, Node.js, Auth0-integrated web flows Cloud / Delivery: AWS, Docker, GitLab CI Observability / Operations: New Relic, Rootly, Playwright AI / ML: OpenAI, AWS Bedrock