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AI QA Engineer

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Posted on Oct 17

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Apple

AI QA Engineer

Posted 22 days ago

Apply on company site View full job

Why you should apply for a job to Apple:

Ranked as one of the Best Technology Companies in 2020
3.7/5 in overall job satisfaction
3.1/5 in supportive management
66% say women are treated fairly and equally to men
65% would recommend this company to other women
66% say the CEO supports gender diversity

Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›

Are you passionate about delivering flawless and resilient software experiences to millions of users? At Apple, we are seeking a versatile Quality & Operations Engineer who possesses a unique blend of skills across quality assurance, live system troubleshooting, and a solid understanding of LLMs. In this critical role, you will act as the technical linchpin for highly advanced software ecosystems. Your primary focus will be on designing robust QA testing strategies, uncovering complex system bugs, driving deep root-cause analysis across the tech stack, and maintaining smooth operational workflows. Additionally, you will leverage your knowledge of LLMs to build smart tools and optimize our engineering processes. If you excel at navigating ambiguity, love connecting the dots between user-facing behaviors and backend services, and thrive in dynamic environments, we want you to join our team.

Description
As a AI Quality Engineer, you will be the cornerstone of our team's technical resilience. Your capabilities will span proactive quality assurance, system troubleshooting, and live operational support:

* Proactive Quality Assurance & Testing: Apply strong QA methodologies to design, automate, and execute rigorous testing strategies. You will proactively identify hidden system anomalies, functional bugs, and quality degradation in complex software workflows before they impact the end-user experience.
* Deep Root-Cause Analysis & Triaging: Leverage a balanced skill set to navigate complex, multi-tiered architectures. You will trace issues from backend services down to client-side logs, pinpointing the exact origin of complex defects across the entire tech stack.
* AI-Empowered Development & Tooling: Utilize your fundamental understanding of generative AI (e.g., LLMs) to develop internal tools, scripts, and automation frameworks. You will integrate LLM capabilities into our operational workflows to boost testing efficiency, log analysis, and daily productivity.
* Live Operations & Incident Response: Act as a critical line of defense during technical escalations. Demonstrate strong operational readiness to monitor service health, investigate live system anomalies, manage time-sensitive inquiries, and drive production issues to resolution.
* Infrastructure & Automation Optimization: Maintain, optimize, and enhance existing QA automation frameworks, CI/CD pipelines, and basic monitoring tools to scale our testing posture.
* Cross-Functional Remediation: Collaborate seamlessly with internal engineering, machine learning teams, and third-party partners. Spearhead joint debugging efforts and translate complex technical findings into actionable, permanent systemic fixes.

Preferred Qualifications
Proficiency in scripting and automation languages (e.g., Python, Bash) to build and optimize testing tools, operational workflows, or LLM-based utility scripts.
Familiarity with building light-weight AI applications (e.g., Agentic coding, or similar frameworks) for productivity.
Experience with software compliance, technical audits, or regional operational rollouts.
A proactive, hands-on mentality with a passion for building scalable, robust quality and operational processes.
Highly adaptable and resilient, with the ability to maintain composure and drive solutions during critical software incidents.

Minimum Qualifications
BS/MS in Computer Science, Software Engineering, Information Systems, or equivalent practical experience.
Solid foundation in Computer Science with a highly balanced technical background spanning Quality Assurance, Software Troubleshooting, and System Operations.
Strong proficiency in testing and debugging complex, distributed systems, with the proven ability to isolate bugs spanning from backend services to client applications.
Fundamental knowledge of generative AI concepts (such as LLMs), with the ability to utilize AI models via APIs for software development, automation scripting, and process optimization.
Demonstrated experience in QA automation, live incident response, and driving technical escalations to resolution in a fast-paced environment.
Practical experience reading and interpreting client-side logs (e.g., iOS/macOS environment) for effective end-to-end triaging.
Excellent analytical, root-cause analysis, and communication skills, capable of translating complex system logs into clear insights for diverse technical and non-technical teams.

About Apple

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

Size: 10,000+ employees
Industry: Technology: Manufacturing

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