About the role
We’re looking for a full-stack Python engineer to join our Central Operations team.
Central Ops sits across our core products (Cards, Loans and Motor), focusing on shared operational challenges and opportunities. We build a mix of internally facing web applications and robust automations to help our Operations teams deliver great outcomes for customers, efficiently and at scale.
It’s a broad space: Operations makes up roughly half of our employee headcount and covers everything from day-to-day customer support up to complex areas like Fraud and Fincrime prevention. As our customer base grows rapidly, our role is to help ops keep pace without relying solely on headcount growth. We make intelligent, pragmatic use of AI where it adds real value, working closely with Product, Data Science and Analytics to deploy solutions that genuinely support our ops agents.
You’ll have real ownership from an engineering perspective, shipping features that are used daily by Ops teams. It’s an evolving space at Lendable, and what you build will help shape both our tools and our technical direction.
Some examples of things we’ve built recently:
Rebuilt our Ops QA admin system from the ground up, replacing an off-the-shelf tool with something tailored to our needs
Deployed a pipeline to summarise customer calls into concise notes using LLMs, automatically surfaced in ops admin panels — removing the need for manual note-writing
More than doubled the number of complaints processed by agents through a combination of targeted AI automation and improved UX
What we’re looking for
We’d consider the following essential to the role:
Solid experience with Python in a web application context. You have some experience with web frameworks like FastAPI, Django or Flask. We use FastAPI.
Experience with Javascript/Typescript and a modern JS framework such as React, Angular or Vue.js. We generally use React & NextJS
Strong engineering principles & practices: design patterns, testing, clean code and a good reviewer
Previous experience working in a product-focused team
A keen desire to want to learn and input into a highly collaborative team
A desire to learn about and experiment with Generative AI and LLMs. Actual experience is a plus
The following are also a plus, but by no means essential. If you don’t meet all of these, please apply anyway!
You use AI tools like Copilot, Cursor, Claude or others in your day-to-day coding
Exposure to Domain Driven Design, Message-Driven Systems and Event Sourcing
Experience with cloud infrastructure, particularly AWS
SQL, and finding your way around data schemas
Shipping containerised software with Argo, Kubernetes, Docker and Terraform
Skill with CSS and exposure to Tailwind
Interview process
Introductory call
Take home Task
Technical Interview
Cultural/behavioural interview
