Job Description
Lyst are looking for software engineers with experience using Python to build a checkout architecture which allows you to order from multiple retailers using a simple API.
Lyst is a technology platform that revolutionises the way people shop for fashion. We connect millions of consumers globally with the world’s leading fashion designers and stores, giving them a simpler, more engaging and more effective shopping experience. Lyst has grown over 300% every year since launch in 2011 and has raised over $60M from top-tier investors including Accel, DFJ, Balderton and the teams behind LVMH, Michael Kors and Oscar de la Renta.
The main challenge now is to build a scalable architecture, meaning we have to tackle the challenges that come with using Python for distributed systems; consistency, availability, service orchestration and much more.
- Building the integrated payment and checkout system using Python as well as the latest tools, technologies and methodologies.
- Supporting partner integration teams and ensuring that integration with partner retail checkout systems and APIs is easy and effortless.
- Integrating with third‑party payment systems such as Stripe, Klarna, Apple Pay, etc.
- Developing a secure data management and CRM system for internal and external stakeholders (OWASP guidelines, etc.).
- Creating new ways to automate onboarding for retailers that comply with global regulations.
How we work
We are developing an environment and culture that is all about writing great software using the best tools in the best possible manner. We like to build things that solve problems, and you will not be constrained by process – we work in small product teams that take a lean approach to building things.
Qualifications
In this team we’re looking for engineers who are excited to work on secure technologies in a Python environment. You will ideally have plenty of experience using:
- Kanban and Scrum methodologies (Jira), depending on whether the team is more customer facing or internal.
Additional Information
- 50 engineers and data scientists.
- 5M duplicated products detected and merged using product image features.
- 72k crowd‑sourced labels generated per day.
- 500k recommended products per day.
- 120 EC2, 8 RDS, 7 ElastiCache, and 10 Redshift instances.
- Our internal analytics system collects about 100M data points per day.
- 40+ merged pull requests per day.
- 20k lines of change per week.
- Lots of open source projects (https://github.com/lyst and https://github.com/SSAW).
- Opportunities to get invited to speak at events such as PyCon, EuroPython, and PyData.
- Feature toggling and A/B testing.
