SummaryPosted: Feb 19, 2025Weekly Hours: 40 Role Number:200591850The Apple Data Platform team enables data analytics, machine learning, and feature engineering for products like Siri, Search, Music, and iCloud, providing a secure, reliable, and user-friendly infrastructure for data-driven innovation. As a Staff Engineer on the Platform Efficiency team, you will design AI-powered solutions, including advanced data insights and unified search. We seek an experienced AI-Driven Observability Engineer to enhance service team performance through AI-driven observability and metrics. In this role, you will refine anomaly detection, streamline incident response, and improve operational efficiency by leveraging observability data from platforms like Splunk, CloudWatch, and Datadog. Additionally, you will collaborate with cross-functional teams to optimize platform cost and performance using data-driven strategies. Your work will accelerate the adoption of the Apple Data Platform, supporting teams across Apple and enriching the experience for millions of users. DescriptionDescriptionYou will drive platform efficiency initiatives for the Apple Data Platform, focusing on developing control planes for data-intensive workloads, analyzing performance, identifying and eliminating bottlenecks, defining key performance metrics, and building observability services across hybrid and multi-cloud environments. You will work closely with Apple leadership, providing data-driven insights to support strategic decision-making. We are looking for a skilled AI-Driven Observability Engineer to enhance service team performance through AI-driven observability and metrics. In this role, you will improve anomaly detection, incident response, and operational efficiency by leveraging observability data from platforms such as Splunk, CloudWatch and internal data sources, while optimizing platform cost and performance through collaboration with cross-functional teams and data-driven strategies. Key Responsibilities: - Design, develop, deploy, and manage large-scale, enterprise-grade distributed data platform infrastructure. - Diagnose and resolve infrastructure lifecycle challenges to ensure high availability and optimal performance. - Implement AI-driven monitoring and alerting systems to enhance observability for data infrastructure applications. - Leverage AI and analytics to improve anomaly detection, incident response, and system reliability. - Collaborate with cross-functional teams to identify inefficiencies and optimize data platform performance at scale. - Maintain comprehensive documentation, including APIs and user guides. - Stay informed on emerging open-source monitoring solutions and industry best practices to continuously improve platform efficiency.Minimum QualificationsMinimum Qualifications10+ years of software development experience.3+ years of experience as a technical lead, guiding teams through complex design decisions and setting high standards for code quality, performance, and scalability.Deep expertise in Large Language Models (LLMs) and their application in AI-driven solutions.Proven track record in managing and optimizing Big Data & AI platforms, driving adoption through innovative, value-added solutions.Proficiency in programming languages such as Python, Java, and Scala, particularly in the context of data processing and AI integration.Strong organizational skills with the ability to collaborate effectively across large cross-functional teams to drive key product innovations.Demonstrated ability to influence and drive product development, with a passion for operational excellence and automation.Exceptional problem-solving skills and the ability to thrive in a fast-paced, dynamic environment.Key QualificationsKey QualificationsPreferred QualificationsPreferred QualificationsExperience in AI agent orchestration, enabling seamless integration of AI models to automate processes and improve workflow efficiency across various business applications.Deep expertise in AWS Cloud services and infrastructure.Practical experience using Kubernetes as an orchestration layer for managing workloads.Familiarity with streaming data processing frameworks such as Apache Flink, Kafka Streams, and Spark Streaming.Education & ExperienceEducation & ExperienceAdditional RequirementsAdditional RequirementsPay & BenefitsPay & BenefitsAt Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $175,800 and $312,200, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.