Quality Engineer Mobile Automation & AI Tooling

Quality Engineer

• Mobile Automation & AI Tooling 2728 Orchard Parkway, San Jose, CA 95134 Hybrid work $46 an hour
• Full-time $46 an hour
• Full-time Role Summary We are looking for a hands-on Quality Engineer with strong mobile automation and software engineering skills to help build, maintain, and validate automated testing workflows for client products.

This role is focused on test automation, mobile device validation, QA tooling, and AI-assisted testing implementation. The ideal candidate is comfortable writing code, debugging test failures, working with mobile automation frameworks, and helping integrate AI-based tools into existing QA workflows. They should be comfortable using AI tools and APIs at the implementation layer to support testing, validation, reporting, and automation. Expectations You will help create and maintain automated QA workflows across mobile, web, and internal test systems. The role will involve writing automation code, debugging failed test runs, validating results, and helping engineering teams improve reliability.

This may include:

Mobile automation using Appium, Selenium, WebDriver, WDA, XCUITest, Android tooling, or similar systems Python-based automation scripts, test runners, validators, and reporting tools React-based dashboards or internal QA interfaces Hack/backend integration within a typical Meta-style engineering stack Device log review, screenshot comparison, OCR workflows, and automated result validation AI-assisted testing workflows using existing APIs, prompts, structured outputs, or internal tools Translating manual QA workflows into repeatable automated systems Core Responsibilities Build and maintain automated tests for mobile applications and device-based workflows Write Python scripts and automation tools for test execution, validation, and reporting Work with Appium, Selenium, WebDriver, or similar automation frameworks Debug automation failures across devices, apps, logs, APIs, and test infrastructure Support React-based QA dashboards and internal tools as needed Work with Hack/backend services in a Meta-style development environment Integrate AI-assisted testing tools at the implementation layer Validate AI-generated or automation-generated outputs for accuracy and consistency Review screenshots, logs, OCR output, device behavior, and test results Clearly document bugs, regressions, edge cases, and automation failures Collaborate with engineering and QA leads to improve test reliability and coverage Must-Haves 3+ years of experience in QA automation, software engineering, mobile testing, or related technical roles Strong programming ability in Python Experience with mobile automation frameworks such as Appium, Selenium, WebDriver, WDA, XCUITest, or Android automation tooling Familiarity with React for internal dashboards, tools, or frontend debugging Familiarity with Hack or willingness to work within a Meta-style backend stack Strong understanding of APIs, logs, debugging workflows, and test infrastructure Ability to investigate failures across app behavior, automation scripts, device state, and backend systems Strong written communication for bug reports, regression summaries, and technical findings Comfortable working onsite with engineering and QA teams Nice-to-Haves Experience testing or automating

AR/VR/XR

devices Experience with physical device labs, mobile device farms, or hardware-adjacent QA Experience with iOS and Android automation at scale Familiarity with screenshot comparison, image diffing, OCR, or visual validation workflows Experience integrating AI tools or LLM APIs into QA workflows Experience with structured AI outputs, prompt-based validation, or automated report generation Experience with internal developer tools, dashboards, or test orchestration systems Experience working in large-scale engineering environments or Meta-style development workflows Calling existing AI APIs or internal AI services Using AI outputs inside QA workflows Validating AI-generated test results Helping turn AI-assisted testing ideas into usable engineering tools Debugging where AI-assisted automation succeeds or fails

Pay:

$46.00 per hour

Benefits:

401(k) Dental insurance Flexible schedule Health insurance Paid time off Retirement plan Vision insurance

Work Location:

Hybrid remote in San Jose, CA 95134