About the role
We are seeking high-performing London-based engineers of any level to help us solve more of our customers’ problems. We are looking for folks who are excited about designing elegant technical solutions and shipping great code frequently. If you are looking for a fresh challenge at a fast-growing AI startup - we would love to hear from you!
What You’ll Do
This is a hands-on (‘individual contributor’) role focused on building product that will solve our customers’ problems, including specifically:
- Designing, building and maintaining backend services and APIs
- Designing and building new UI/web components
- Developing new integrations to third party services and AI models
- Help triage bugs, investigate production incidents, and contribute to postmortems and root cause analysis
- Participating in code reviews, collaborating across technical and non-technical teams and stakeholders
What We’re Looking For
Our ideal hire will:
- Enjoy -actually- building and making an impact: you get a kick out of shipping code frequently, iteratively, and collaboratively. You value MVPs and customer impact over perfectly engineered systems. You can take responsibility over the end-to-end deployment of what you build.
- Thrive at solving tough technical problems: you enjoy breaking down challenges into simple and well-designed solutions. You are fact-oriented and thoughtful in your approach, but you don’t get bogged down in over-intellectualizing or over-complicating things.
- Scale-oriented: while having a bias to action and impact, you will care about scalable infrastructure and engineering processes. Even better if you’re able to bring some better practices or improvements to our infrastructure or ways of working!
- : we try to balance speed and impact with fitting the best framework/ technology to the task at hand. Currently, we work primarily in Python / Flask / FastAPI on the backend, Terraform / GCP / AWS for infra, and React / JavaScript / TypeScript / Vercel on the frontend. Ideally, you’ll be able to contribute within our stack while also helping us experiment and evolve to continually improve functionality and performance.
