Job Description & Details
This is an interesting shift from traditional software engineering roles because they want someone who actually embraces AI tooling like Claude Code and GitHub Copilot as a core part of their daily workflow. If you are already living in your IDE prompting your way through boilerplate and unit tests, this gig leans right into your strengths.
What You'll Actually Be Doing
You will spend your days building and maintaining Python applications while actively leveraging Generative AI assistants to accelerate delivery. Don't expect to just prompt your way to a finished product, though—you'll be heavily reviewing AI-generated code for security vulnerabilities, edge cases, and maintainability. Much of your time will go toward writing clean Python, spinning up unit tests, debugging tricky integration issues, and collaborating inside an Agile sprint cycle.
The Core Tech Stack
Your bread and butter here is intermediate-level Python paired with modern AI coding assistants like Anthropic Claude Code and GitHub Copilot. The team expects you to know your way around Git and GitHub for version control, understand REST API design, and have a solid grip on object-oriented programming fundamentals. If you've tinkered with FastAPI or Django, worked with SQL databases, and understand basic CI/CD pipelines or Docker containerization, you'll slot right in without a massive learning curve.
Interview Expectations
Expect the hiring managers to test both your foundational Python chops and your ability to prompt-engineer effectively. They will likely hand you a messy snippet of AI-generated code and ask you to spot subtle security flaws or logical bugs that the LLM missed. They want to see that you act as an intelligent editor rather than a blind copy-paster, so be ready to explain how you validate and refactor AI outputs under tight constraints.
Application Advice
Skip the generic resume filler and make sure your application explicitly highlights your hands-on experience with Claude Code, GitHub Copilot, or similar LLM developer tools alongside your core Python projects. Drop keywords like 'AI-assisted development,' 'prompt engineering,' 'unit testing,' and 'Agile/Scrum' directly into your experience bullets to ensure you clear the automated ATS screens. Show them you know how to leverage AI to code faster without sacrificing software quality.