Quality Engineer, Rights & Pricing

The Rights & Pricing engineering team provides the Apple Services platform for distribution rights by country, calculation and management of prices including retail, offers, wholesale, and tax. The Pricing QA team ensures the quality, reliability, and scalability of complex backend pricing systems that power Apple Services across multiple products and regions. We are looking for a highly skilled and hands-on Quality Engineer who is passionate about delivering high-quality software through strong technical depth, thoughtful test strategy, and scalable automation. In this role, you will work closely with Engineering, Product, and Quality teams to validate backend services, APIs, and pricing workflows across Apple Services. You will contribute to test planning, exploratory testing, automation development, and release validation while gaining experience working within large-scale distributed systems. The ideal candidate has a strong technical foundation, curiosity to learn complex systems, and interest in building scalable automation solutions while maintaining a strong focus on customer impact and product quality.Execute functional, integration, regression, and exploratory testing for backend services, APIs, and pricing workflows across Apple Services Develop and maintain automated tests and test utilities for backend systems, using maintainable, well-structured code that integrates into shared test infrastructure Collaborate with Engineering and Product partners during feature design and development to understand requirements, identify testability gaps, and define coverage strategies Debug failures across APIs, services, log output, and test environments using structured diagnostic approaches, and document findings to support root cause resolution Contribute to CI/CD pipeline automation, including test integration, execution reporting, and release validation workflows Measure and improve test reliability, automation coverage, and execution efficiency using defined quality metrics Participate in test planning sessions, feature reviews, and quality discussions across the development lifecycle Evaluate and apply AI-assisted testing tools (e.g., automated test case generation, coverage gap analysis) where they reduce manual overhead and accelerate feedback cycles Produce structured quality status updates, risk summaries, and release readiness assessments for engineering and cross-functional stakeholders2+ years of professional experience in software quality engineering, QA automation, software testing, or a closely related software engineering discipline Programming proficiency in Python or another modern, object-oriented language (e.g., Java, Kotlin, Go), with the ability to write readable, maintainable test code Demonstrated experience testing backend systems, REST APIs, or service integrations, including validation of response contracts, error handling, and data integrity Hands-on experience writing and maintaining automated tests using a structured framework (e.g., pytest, JUnit, TestNG, or equivalent) Working familiarity with REST API concepts and tooling -- including HTTP methods, status codes, request/response structure, and tools such as Postman, curl, or equivalent Working familiarity with CI/CD pipeline concepts and how automated tests integrate into build and release workflows (e.g., Jenkins, GitHub Actions, GitLab CI, or equivalent) Ability to debug and investigate failures across application logic, API behavior, data state, and test infrastructure using logs, error output, and systematic isolation techniques Foundational understanding of software development lifecycle methodologies and how quality engineering activities map to design, development, and release phases Bachelors degree in Computer Science, a related technical field, or equivalent practical experienceExperience with pytest or comparable backend automation frameworks, including fixture management, parameterization, and test organization patterns Experience validating complex business logic in pricing systems, financial workflows, transactional systems, or billing platforms -- including boundary condition and edge case analysis Experience with data validation and SQL, including querying databases to verify data accuracy, transformation correctness, and system-of-record consistency Familiarity with distributed systems or service-oriented architectures, including an understanding of how failures propagate across service boundaries Familiarity with cloud and containerized environments such as AWS, GCP, Kubernetes, or Docker, particularly in the context of test environment setup and debugging Experience with observability and debugging tooling, including structured log analysis, metrics dashboards (e.g., Grafana, Datadog), or distributed tracing platforms Experience evaluating or applying AI-assisted testing tools for use cases such as test case generation, anomaly detection, or coverage analysis Ability to communicate technical quality findings to both engineering and non-engineering stakeholders, adapting level of detail and framing to the audience Experience contributing to test strategy documentation, including risk-based test plans, coverage matrices, or release readiness checklists