Coursera was launched in 2012 by Andrew Ng and Daphne Koller with a mission to provide universal access to world-class learning. It is now one of the largest online learning platforms in the world, with 183 million registered learners as of June 30, 2025. Coursera partners with over 350 leading university and industry partners to offer a broad catalog of content and credentials, including courses, Specializations, Professional Certificates, and degrees. Coursera’s platform innovations enable instructors to deliver scalable, personalized, and verified learning experiences to their learners. Institutions worldwide rely on Coursera to upskill and reskill their employees, citizens, and students in high-demand fields such as GenAI, data science, technology, and business. Coursera is a Delaware public benefit corporation and a B Corp.
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Job Overview:
The Content Discovery Group is focused on connecting the right learner to the right content at the right moment. We are a metrics-obsessed team where engineers constantly balance the need to prove or disprove hypotheses quickly while also setting ourselves and our sister teams up for long-term agility and ability to scale to a global customer base. Working across high-criticality surfaces like search, the home page and our product detail page we partner with Product, Data Science and Machine Learning to create personalized discovery experiences. We’re looking for engineers that value simplicity in solutions but do not shy away from complexity when the data is telling us there is an opportunity if we can meet it.Your responsibilities:
- Work cross-functionally with engineering, product, design, and data teams to inform a roadmap that balances long-term and short-term priorities, based on both big-picture perspective as well as data-informed learnings
- Develop an architecture that efficiently addresses business challenges such as emergent complexity, leveraging foundational knowledge of design patterns and practical experience
- Promote sustainable architectural solutions by establishing and advocating for core principles, documented through decision records on API design, data storage strategies, and other key choices
- Apply industry best practices and system design expertise to guide local design decisions through collaboration and reviews with engineers
- Mentor and guide fellow engineers to help them improve their technical ability and become more effective product software engineers
- Initiate and lead high-leverage projects to raise the quality bar for how we work and what we deliver (e.g. by improving developer productivity, and/or the quality, performance, availability, and resiliency of our systems and teams)
- 8+ years of experience working in a relevant product software engineering role
- 3+ years of experience leading an engineering pod, evaluating success, and adapting these choices to changing product and business needs
- Expertise in designing highly-scalable and performant full-stack applications, microservices, and storage layers using common frameworks, languages, and infrastructure (e.g. Java, MySQL, NoSQL, Kafka or equivalent)
- Knowledge of professional software engineering and best practices for the full SDLC, including technical design, coding standards, code reviews, source control management, build processes, testing, documentation, and operations
- Able to communicate effectively at multiple levels of abstraction to both technical and non-technical stakeholders, both verbally and in writing
- A strong sense of ownership and conscientiousness, with a strong desire to learn about products, people, and technology; proactive and action-oriented
- Strong empathy for both engineers and cross-functional partners, to enable the right balance of inquisitive information-gathering and timely decision-making in order to identity problems, overcome ambiguity, and align others on a solution
Bonus qualifications:
- Experience in hybrid teams supporting both external user-facing web products and internal platforms to enable other teams
- Expertise in technologies like ReactJS, GraphQL/DGS, DynamoDB, and Redis for designing scalable and high-performance applications end-to-end
- Experience with generative AI tools and supporting processes and systems; proficient in identifying opportunities enabled by emerging technologies while managing production needs for quality and scalability
- Strong track record of leadership and mentorship, preferably in a remote environment
- Experience with teams with diverse identities and working styles, tailoring approaches to bring out the best contributions from each individual teammate
If this opportunity interests you, you might like these courses on Coursera:
- Object Oriented Java Programming: Data Structures and Beyond
- Designing data-intensive applications
- Communication Skills for Engineers
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