10 years ago
London, United KingdomMid Level
Responsibilities
- Build and maintain client-side JavaScript features and responsive mobile-first user experiences.
- Solve technical problems using JavaScript and, where needed, Python and Django.
- Collaborate with product managers and designers to develop new features.
- Build and maintain internal tools and dashboards, including server-rendered pages and EmberJS applications.
- Contribute to open-source libraries created or used by Lyst.
- Improve front-end build processes to make deployment and iteration faster.
- Write unit and integration tests and ensure code is reliable and bug free.
- Take ownership of committed code and contribute to engineering culture, collaboration, and continuous improvement.
Requirements
- Experienced JavaScript engineering experience, including client-side development.
- Experience or interest in Python and Django for server-side development.
- Ability to work with responsive, mobile-first web experiences and progressive enhancement.
- Familiarity with CSS and front-end tooling such as LESS, Grunt, RequireJS, Browserify, ESLint, Karma, Mocha, and Sinon.
- Interest in collaborating across engineering, product, and design disciplines.
- Commitment to writing maintainable, reliable software and contributing to a collaborative team culture.
Benefits
- Training and mentoring to support professional growth.
- Opportunities to attend industry events including FOSDEM, JS Conf, and LNUG.
- Encouragement to participate in the wider engineering community and contribute to open source.
- Clothing allowance to spend through the Lyst site.
- The role is based at Lyst’s team location in Hoxton Square.
Tech Stack
Categories
About Lyst
Lyst builds a global fashion shopping and search platform that aggregates premium and luxury products from thousands of brands and retailers, earning revenue from referrals and checkout transactions. Founded in 2010 and headquartered in London, it was acquired by Zozo in 2025. The service lists over 8.5 million items from 17,000+ brands for roughly 200 million shoppers, and relies heavily on machine-learning search and recommendations.