Job Description & Details
This is a hands-on software engineering role designed for developers who are already leaning heavily into AI-assisted workflows using tools like Claude Code and GitHub Copilot. You'll be expected to move fast, write clean Python code, and leverage LLMs not just as a novelty, but as a core multiplier for your daily shipping velocity. If you are still writing every line of boilerplate manually, this will feel like a steep climb.
What You'll Actually Be Doing
Your day-to-day will revolve around building, testing, and iterating on Python applications while integrating modern AI tooling directly into your engineering loops. You'll spend less time wrestling with routine syntax and more time architecting solutions, debugging complex edge cases that Copilot misses, and orchestrating prompts in Claude Code to scaffold entire features. The real challenge here isn't just writing code—it's maintaining codebase hygiene, architectural integrity, and security while moving at the accelerated pace that AI tooling affords.
The Core Tech Stack
Python is your bread and butter here, and you need to be comfortable writing intermediate-level code that scales without falling apart under pressure. Beyond standard Python proficiency, the non-negotiable differentiator for this role is your fluency with intermediate Anthropic Claude Code and GitHub Copilot workflows. The team expects you to know how to effectively prompt, constrain, and guide these models to avoid hallucinated dependencies, write comprehensive unit tests, and refactor messy codebases without breaking production.
Interview Expectations
Expect the interviewers to skip the standard computer science trivia and instead drop you into a live coding session where you'll be evaluated on how you collaborate with an AI assistant in real time. They will likely ask you to debug a deliberately broken Python service while sharing your screen, watching closely to see how you prompt Claude or Copilot to find the root cause. They aren't just looking for a working script; they want to see your mental model for validating AI-generated code, catching subtle logic errors, and knowing when to ignore the model's output and write the logic yourself.
Application Advice
When updating your resume for this role, skip the generic buzzwords and clearly highlight your practical, hands-on experience using AI coding assistants in production environments. Explicitly mention Python frameworks you've built, and weave in terms like AI-assisted development, prompt engineering for code generation, Claude Code, and GitHub Copilot directly into your project descriptions. ATS filters will look for the intersection of Python and AI tooling, so making those workflows prominent will ensure your profile lands on the hiring manager's desk.