Senior Quality Engineer, Demo Platforms & OS Automation

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Sunnyvale, CA
Salary: $175,500–$311,700 / yr
Posted: 15 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $182k

This role $244k

$104k most similar roles pay here $334k

This role pays more than 92% of similar roles. Most pay $151,000–$213,200 — the shaded band above. At the midpoint, this role pays about $244k versus about $182k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · Senior Quality Engineer, Demo Platforms & OS Automation

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As a Senior Quality Engineer, Demo Platforms & OS Automation, you will join the Retail Technology, QA Engineering team to manage quality standards for customer-facing interactive systems and apps. You will own quality across demo delivery pipelines, designing and maintaining end-to-end automation for bundle composition, OTA distribution, and OS-regression cycles. Your daily work involves partnering with cross-functional teams to influence tooling design, shape diagnostic surfaces, and make critical go/no-go release decisions based on defect trends. You will utilize Python, Swift, Jenkins, TeamCity, GitHub, Docker, Kubernetes, and Ansible to validate software across iOS, iPadOS, macOS, watchOS, tvOS, and visionOS. This role addresses the complex intersection of operating systems and store demo environments, ensuring reliable performance for hardware, content management systems, and experience frameworks across a global network of interactive platforms.

Skills

Python Swift iOS iPadOS macOS watchOS tvOS visionOS CI/CD Jenkins TeamCity GitHub Docker Kubernetes Ansible Test Automation Log Analysis OTA Distribution

What you'll do

Set the strategy and quality bar for bundle composition, OTA distribution, and OS-regression validation across all platforms.
Design, author, and maintain end-to-end automation for bundle and OTA pipelines including installation and runtime behavior.
Lead OS regression testing for every major release to validate bundles, content, and tooling.
Influence engineering partners on tool design to improve log visibility and diagnostic surfaces.
Identify, report, and collaborate with partner teams to resolve bugs across multiple layers of the system.
Translate coverage data and defect trends into clear go/no-go release decisions for leadership.
Develop and maintain automated test frameworks using Python and Swift while managing legacy code.

What we're looking for

7+ years of experience in software quality engineering, test automation, or software development.
Demonstrated technical leadership defining quality strategy and partnering with engineers to influence tooling design.
Experience mentoring QA engineers on automation and build-pipeline literacy.
Proficiency in Python and Swift, including the ability to improve legacy code and drive fixes.
Proven experience designing, building, and maintaining end-to-end test automation frameworks paired with exploratory testing skills.
Experience validating across multiple Apple platforms (iOS, macOS, watchOS, tvOS, visionOS) and managing hardware fleet configurations.
Proficiency in CI/CD pipelines and version control tools like Jenkins, TeamCity, GitHub, Docker, and Ansible.
BS in Computer Science, Computer Engineering, or equivalent practical experience.
Experience validating against pre-release software and beta builds (preferred).
Ability to navigate disclosure constraints and work through ambiguity (preferred).
Experience testing AI/ML features or leveraging AI in workflows (preferred).

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