Site Reliability Engineer - AI & Data Platforms

Job Summary

Site Reliability Engineer - AI Data Platforms. Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, is the result of us making each other s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you ll do more than join something - you ll add something. Do you want to help build some of the largest and most consequential enterprise and customer technology systems in the world Join Apple s Information Systems and Technology (IST) organization. IST is the engine behind everything Apple does for customers and for the people who build for them. It s Apple s central nervous system. Supporting 2. 5 billion active Apple devices, processing billions of secure transactions, and keeping the technology that defines modern life running flawlessly, IST makes the impossible feel effortless. Do you love building solutions to handle global complexity and immense scale Imagine what you could do here. AI Data Platforms (AiDP) is ISTs engine for AI-powered innovation. The team brings together data, application development, and machine learning - including generative AI - along with data services and customer success functions, to help IST build solutions more efficiently and streamline the adoption and embedding of generative AI across Apple.

Responsibilities

• Design, develop, and automate: Build tools, frameworks and solutions to improve reliability, scalability, and efficiency across large scale distributed data platform systems.
• Monitor and maintain: Implement advanced monitoring and alerting for on-prem , cloud and workloads.
• Troubleshoot and solve: Support critical applications including analytics, reporting, and AI/ML apps.
• Respond to and resolve complex production incidents, and perform root cause analysis.
• Collaborate: Work closely with development and operations teams to integrate reliability best practices throughout the software lifecycle.
• Optimize: Proactively recommend improvements in architecture, deployment, and operations for distributed systems.

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