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The Coach team is leading Coursera’s AI initiatives by developing a GenAI platform that enables rapid creation, deployment, and management of LLM-powered features across the organization. In the coming quarters we’re looking to introduce exciting new capabilities on the platform, including a multi-agent workflow builder, improving and expanding our RAG pipeline, adding new modalities such as audio, image, video generation, and building out a UI component library that can present a unified AI experience on multiple surfaces. As a fullstack engineer, you’ll have the unique opportunity to shape and build both backend systems and frontend experiences, to deliver meaningful impact.
Job Responsibility:
Design and implement scalable & robust frontend and backend applications, bringing a clean, consistent, and high-quality look and feel to every step of the learner journey
Integrate with leading model providers (OpenAI, Gemini, etc.) and evaluate trade-offs between models
Design and implement data pipelines that feed LLMs, embeddings, and retrieval systems
Use and explore AI-powered coding and design tools to accelerate delivery and creativity
Measure your work thoroughly, analyze results, and generate hypotheses to drive new product changes through A/B testing
Upgrade critical and legacy UI components, improving accessibility, performance, and visual polish
Collaborate closely with design, business, and product stakeholders to find the best solutions and adapt to changes
Share knowledge and guide other teams in using the design system and visual standards on the frontend, and in using the platform to power LLM based features on the backend
Requirements:
5+ years of professional software engineering experience building web applications
Solid experience across both frontend and backend (for example: React/TypeScript on the frontend and Java or similar on the backend)
Has designed, built, and owned end‑to‑end features or systems in production
Deep understanding of API design (REST and/or GraphQL), service-to-service communication, and microservice architectures
Familiar with modern engineering practices such as code review, testing, and CI/CD, and working in a cloud environment
Nice to have:
Familiar with prompt engineering, context engineering, model APIs, embeddings, tokenization, guardrails, and quality evaluation
Loves innovating and is curious about AI-assisted development
Balances long-term design thinking with quick execution on urgent goals
Communicates clearly and enjoys working closely with Product, Design, and other partners on shaping the work
Passionate about performance, accessibility, and visual details
What we offer:
competitive pay and equitable compensation practices