Senior Python Engineer - AI-Driven Ops & Automation

Remote Worker LTD.; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Flexible working

Hybrid roles

Private health coverage

Retirement savings

Employee referral programme

Office meals & snacks

Job summary

Lendable is hiring a full-stack Python engineer for its Central Operations team. You’ll work across Cards, Loans and Motor, building web apps and automations to support ops at scale.

Expect real ownership from an engineering perspective, shipping features used daily by Ops teams and collaborating with Product, Data Science and Analytics to deploy value-driven solutions. Hybrid working model offered.

Qualifications

• 8+ years of professional experience as a software engineer.
• 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
• You use AI tools like Copilot, Cursor, Claude or others in your day-to-day coding

Responsibilities

• You will own features shipping that are used daily by Ops teams.
• Collaborate with Product, Data Science and Analytics to deploy solutions that support ops.
• Build and maintain internal tooling and automation to improve efficiency.

Skills

8+ years experience

Python

JavaScript/TypeScript

React

Web frameworks (FastAPI/Django/Flask)

Frontend tooling (React/NextJS)

AI tooling in coding

Tools

Docker

Kubernetes

Terraform

Argo

AWS

Job description

Lendable is hiring a full-stack Python engineer for its Central Operations team. You’ll work across Cards, Loans and Motor, building web apps and automations to support ops at scale.

Expect real ownership from an engineering perspective, shipping features used daily by Ops teams and collaborating with Product, Data Science and Analytics to deploy value-driven solutions. Hybrid working model offered.