Category: Artificial Intelligence | Quality Assurance | Machine Learning
Employment Type: Full-Time
Location: Beijing, China
Posted: May 27, 2026
Role Number: 200665346-0351
About the Role
Apple is looking for a talented and driven AI Quality Assurance Engineer to join its engineering team in Beijing. This is a technically demanding, multi-disciplinary role designed for someone who thrives at the intersection of quality engineering, live system operations, and applied AI. You will serve as a critical technical backbone for some of Apple’s most advanced software ecosystems — ensuring that millions of users experience flawless, resilient software every single day.
If you love chasing down elusive bugs across complex distributed systems, have a working understanding of Large Language Models (LLMs), and can stay sharp and decisive during live production incidents, Apple wants to hear from you.
What You Will Be Doing
As an AI QA Engineer at Apple, your responsibilities span the full quality and operations lifecycle — from proactive testing strategy design all the way through to live incident resolution.
Proactive Quality Assurance & Testing You will design, automate, and execute rigorous testing strategies using strong QA methodologies. Your goal is to surface hidden system anomalies, functional bugs, and quality degradation in complex software workflows before they ever reach end users.
Deep Root-Cause Analysis & Triaging You will trace issues across multi-tiered architectures — from backend services down to client-side logs — pinpointing the precise origin of complex defects across the entire technology stack.
AI-Empowered Development & Tooling Leveraging your knowledge of generative AI and LLMs, you will build internal tools, automation scripts, and frameworks that integrate LLM capabilities into operational workflows — boosting testing efficiency, log analysis, and daily engineering productivity.
Live Operations & Incident Response You will act as a first line of defence during technical escalations — monitoring service health, investigating live system anomalies, managing time-sensitive issues, and driving production incidents to full resolution.
Infrastructure & Automation Optimisation You will maintain, optimise, and enhance existing QA automation frameworks, CI/CD pipelines, and monitoring tooling to continuously scale and strengthen the team’s testing posture.
Cross-Functional Collaboration Working alongside internal engineering teams, machine learning teams, and third-party partners, you will lead joint debugging efforts and translate complex technical findings into clear, actionable, and permanent systemic fixes.
Minimum Qualifications
- Education: BS or MS in Computer Science, Software Engineering, Information Systems, or equivalent practical experience
- Strong foundational knowledge in Computer Science, spanning Quality Assurance, Software Troubleshooting, and System Operations
- Proven ability to test and debug complex distributed systems, isolating bugs across both backend services and client applications
- Fundamental understanding of generative AI concepts including LLMs, with practical ability to use AI models via APIs for automation, scripting, and process optimisation
- Demonstrated experience in QA automation, live incident response, and driving technical escalations to resolution in fast-paced environments
- Practical experience reading and interpreting client-side logs (iOS/macOS environments) for effective end-to-end triaging
- Excellent analytical, root-cause analysis, and communication skills — able to translate complex system logs into clear insights for both technical and non-technical stakeholders
Preferred Qualifications
Candidates with the following will be strongly considered:
- Proficiency in scripting and automation languages such as Python or Bash for building and optimising testing tools, operational workflows, or LLM-based utility scripts
- Familiarity with building lightweight AI applications, including agentic coding frameworks or similar productivity tooling
- Experience with software compliance, technical audits, or regional operational rollouts
- A proactive, hands-on mindset with a passion for building scalable and robust quality processes
- High adaptability and composure during critical software incidents
About Apple
At Apple, quality is not a department — it is a culture. Apple is an equal opportunity employer committed to inclusion, diversity, and accessibility as a fundamental human right. Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Every perspective matters, and Apple actively fosters an environment where you can build a career where you truly belong.