About The Position

Join Apple Ads’ System Integration Testing team, which validates revenue-generating scenarios and critical user flows across the Apple Ads platform. As a Tooling Engineer, you will develop tools and automation to make testing faster and more reliable. This includes test data setup utilities, failure analysis tools, reporting dashboards, and AI agent workflows. You will also work on test automation and end-to-end validation to understand the problems your tools solve. The role offers mentorship from experienced engineers and hands-on experience with production systems.

Requirements

  • Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field.
  • Strong coding skills in Swift, Python, and Java for test automation.
  • Experience applying AI/ML concepts to build tools for automated testing, debugging assistance, or code generation that significantly improve developer velocity.
  • Ability to stay updated on emerging technologies such as AI/ML, Model Context Protocol (MCP), and Agentic AI implementations, and apply them to build tools that make tests smarter.
  • Basic understanding of REST APIs, SQL, and data handling formats such as JSON and CSV.
  • Familiarity with Git and basic software development workflows.
  • Strong problem-solving skills and curiosity about how systems work.
  • Clear communication skills and willingness to ask questions and learn.

Nice To Haves

  • Experience building with LLMs, AI agents, or Model Context Protocol (MCP).
  • Experience building CLIs, web dashboards, or reporting tools, such as with Flask, FastAPI, or simple front-end work.
  • Exposure to test automation frameworks such as XCTest/XCUITest, Selenium, Playwright, Cypress, or Appium.
  • Familiarity with CI/CD, cloud platforms such as AWS or GCP, or containerization.
  • Interest in advertising, video streaming, or cross-platform testing across web, mobile, and TV.

Responsibilities

  • Develop tooling and automation to make testing faster and more reliable.
  • Build test data setup utilities, failure analysis tools, reporting dashboards, and AI agent workflows.
  • Work on test automation and end-to-end validation.
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