Senior Python Backend Engineer

We are looking for a Senior Backend Engineer to join the team. In this role, you will contribute to the development and maintenance of custom-built case management applications used by internal stakeholders. These applications are fully developed and maintained in-house and operate entirely within the Azure cloud environment.

You will work within the Back-End chapter as part of a larger multidisciplinary Scrum team consisting of both Backend and Frontend engineers. Although the team is relatively large, work is organised in smaller sub-teams on a quarterly basis to ensure focus, ownership, and effective collaboration.

Responsibilities

Design, develop, and maintain scalable backend services and

RESTful APIs

Define and maintain clear API contracts and specifications

Build integration components and backend services using Python

Work with frameworks and tooling such as

FastAPI, Pydantic, and Pytest

Design and maintain database schemas aligned with application requirements

Write efficient and scalable database queries

Deploy, configure, and operate services within Azure cloud environments

Participate actively in Scrum ceremonies, refinements, and user story discussions

Contribute to code reviews with a coaching and constructive mindset

Collaborate closely with engineers, stakeholders, and other chapters to deliver valuable solutions

What We're Looking For

Strong experience with Python backend development

Experience designing and developing RESTful APIs

Hands-on experience with

FastAPI, Pydantic, and Pytest

Solid understanding of backend architecture and integration patterns

Data & Persistence

Experience designing and maintaining database schemas

Ability to write efficient and scalable complex queries

Experience with Azure or other cloud platforms

Understanding of deploying and operating backend services in cloud environments

Nice to Have - AI-Assisted Development

Experience with AI-assisted development tools and structured AI workflows is considered a strong plus. This includes:

Working with tools such as GitHub Copilot

Creating reusable prompts, templates, and repository-level AI instructions

Embedding team standards and architectural decisions into AI-assisted workflows

Critically evaluating AI-generated output for quality, maintainability, and security

Helping scale structured AI usage across engineering teams

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