QA Automation Engineer Intern — AI-Driven Test Infrastructure

Role Overview
Moon operates without a dedicated QA team. Engineering owns quality — which means automated test coverage is an engineering responsibility, not someone else’s problem. Right now, that coverage needs to grow. As the QA Automation Engineering Intern, you are not a manual tester. You are a developer who builds the infrastructure that lets the team ship with confidence. You’ll build automated test suites, CI/CD test gates, and regression coverage across the React/Capacitor frontend and the .NET

backend. The test infrastructure you build will outlast your internship. That’s the scope of the impact — and the reason this role exists.

About the role

You’ll report directly to the Sr. Engineering Manager, who provides primary mentorship, and

have cross-track exposure to the frontend, backend, and data engineering teams — because your

work spans all of them.

The test code you write is held to the same standard as production code. It gets reviewed,

iterated on, and owned. It is not an afterthought.

This role has outsized impact relative to scope. You’re building infrastructure the whole team

depends on, not a feature that one track uses.

We expect 3 days on-site in Glendale, with flexibility around your academic schedule. Fully

remote is not offered.

AI-assisted test generation is one of the highest-leverage applications of AI tooling in the

engineering workflow. You’ll be expected to use it well — not just use it.

What you'll do

Test Coverage & Infrastructure

Build automated test coverage for the frontend (React/Capacitor components) and backend

(.NET API endpoints).

Establish or extend CI/CD test gates — define and enforce requirements that prevent untested

code from merging.

Create and maintain a regression test suite for core application flows.

Work with each engineering track to identify coverage gaps and close them systematically —

you’re the connective tissue across the full stack.

Document testing standards and coverage expectations for the team so the bar is clear and

repeatable.

AI-Accelerated Quality Engineering

Use AI tools (Cursor, Copilot, Claude) to accelerate test generation — writing tests faster, with

better coverage, s is one of the highest-leverage applications of AI tooling in the

engineering workflow, and it’s a core expectation of this role.

AI-assisted development is your default mode, not an occasional tool — bring the same AI-native

approach to test code that we expect across all engineering tracks.

Evaluate AI-generated test output critically — coverage that looks good but doesn’t catch real

failures are worse than no coverage.

Qualifications

Required

JavaScript/Type Script or C# — coverage needs span both the frontend and backend stacks; you

don’t need both on day one, but you need to be credible in at least one.

Experience with at least one testing framework:
Jest, Playwright, Cypress, xUnit, NUnit, pytest, or

similar.

Understanding of CI/CD concepts:
Git Hub Actions, Azure Dev Ops, or equivalent.

Active AI tool usage — and specifically, genuine interest in how AI can accelerate test generation

and coverage maintenance. This is evaluated explicitly.

You treat test code with the same rigour as production code — not as an afterthought.

Nice to Have

Playwright or Cypress for frontend end-to-end testing.

xUnit or NUnit for .NET backend testing.

pytest for Python pipeline testing.

Experience writing tests for REST APIs.

Exposure to coverage tooling and reporting.

What You’ll Get

Competitive hourly compensation, tiered by experience (undergraduate and graduate rates;

details shared during the process).

Direct mentorship from the Sr. Engineering Manager — plus cross-track exposure to frontend,

backend, and data engineering teams throughout the program.

Work that ships — features you build will go to production users during the internship.

Real code review under the same standards applied to the full-time team — not the kind that

approves everything.

AI tooling stipend (Cursor Pro, Claude Pro, or equivalent) — the AI-native expectation is real; we

remove the financial barrier to getting there.

Priority consideration for full-time roles upon graduation.

Outsized impact relative to your scope: you’re building infrastructure the…