QA Automation Engineering Intern

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, at scale. This 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/TypeScript 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: GitHub Actions, Azure DevOps, 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 whole engineering

team depends on.

Location & Hybrid Policy

This role is based in Glendale, CA. We expect 3 days on-site per week, with flexibility around

academic schedules communicated in advance. Fully remote arrangements are not offered.

Candidates who cannot commit to regular on-site presence in Glendale are not a fit for this program.

How to Apply

Send your resume. If you have testing work to share — a project with automated tests, a CI/CD

pipeline you contributed to, anything — include a link and describe your coverage strategy. No prior

testing project? Write a short paragraph on how you would approach building test coverage for a

REST API that currently has none. Applications are reviewed on a rolling basis.

Moon is committed to building a diverse and inclusive team. We encourage applications from

candidates of all backgrounds, institutions, and experience levels. We evaluate based on

demonstrated ability, not credentials.