Staff Software Developer, Coursera

• If you enjoy owning complex end-to-end features, working at the intersection of product and platform, and building tools that support real human decision-making in an AI era, you’ll thrive here
• 6+ years of professional software engineering experience building web applications
• Solid experience across both frontend and backend (for example: React/TypeScript on the front end and Java/Scala/Python or similar on the back end)
• Has designed, built, and owned end‑to‑end features or systems in production
• Comfortable designing and working with APIs, data models, and service‑to‑service communication
• Familiar with relational and/or NoSQL datastores (e.g., MySQL, DynamoDB) and modern engineering practices (code review, testing, CI/CD)
• Experience working in a cloud environment like AWS or GCP

Desirable

• We’re looking for a Staff Software Developer, Fullstack to help build the next generation of Coursera’s content tools—the systems instructors and partners use to create, review, and improve learning experiences
• You’ll work across the frontend and backend to build workflows that support content creation and maintenance, incorporate AI-assisted suggestions, surface quality signals, and help educators publish updates with confidence
• In this role, you’ll architect and implement user-facing and internal product surfaces, shape the APIs and data flows behind multi-step review processes, and influence how Coursera integrates AI into the content lifecycle in a thoughtful, human-centered way
• Build and own full-stack features used by instructors and creators to design, review, revise, and publish learning content
• Develop and evolve backend services and APIs that power multi-step workflows, versioning, content review logic, and data-rich decision surfaces
• Create clear, responsive interfaces in React/TypeScript that help users understand suggested changes, preview updates, and navigate complex flows
• Integrate with internal AI and evaluation systems so that suggestions, quality checks, and signals are surfaced in a safe, human-in-the-loop way
• Improve the reliability, performance, and cohesion of existing content tools as we modernize and unify the broader authoring and review experience
• Contribute to architectural decisions and establish strong patterns for full-stack development across content tooling systems
• Mentor engineers, guide implementation approaches, and collaborate with product, design, data, and other engineering teams to bring clarity to ambiguous problems and ship high-quality systems