Job Description

The Production Engineering team within the AI and Data Platform (AiDP) organization manages a wide array of real-time, near real-time, and batch analytical solutions. These platforms are integral to core business functions across Apple. These include sales, operations, finance, AppleCare, marketing, and services, and are instrumental in driving critical, data-driven decisions. To build these solutions, we leverage a combination of proprietary and leading open-source technologies such as Kafka, Spark, Iceberg, and Airflow. A key part of our mission is to enable AI-centric automations that enhance the overall efficiency and intelligence of the platform. We are looking for passionate engineers who thrive on solving complex infrastructure challenges at scale, both on-premises and in the cloud. If you are dedicated to optimizing scalable, maintainable, and user-friendly systems, you will find compelling opportunities to make a significant impact at AiDP.

The Service Reliability Engineer (SRE) role within AiDP Production Engineering is a dynamic position that blends strategic architectural design with hands-on technical execution. As an SRE, you will be responsible for configuring, tuning, and ensuring the resilience of complex, multi-tiered systems to achieve optimal application performance, stability, and availability. Our team manages critical data pipelines and applications across both bare-metal and cloud computing platforms, delivering essential data processing for all of Apple’s key business functions. We operate at an immense scale, handling exabytes of data, petabytes of memory, and tens of thousands of jobs to enable predictable and performance data analytics that power features and inform decisions across the company. If you are passionate about designing, building, and running data infrastructure that has a direct and significant impact on Apple’s global business operations, this is the ideal opportunity for you.

Preferred Qualifications

Solid understanding of system design, data structures, and incident management best practices.
Should be able to understand complex architectures and be comfortable working with multiple teams.
Observability tools (e.g: Prometheus, Grafana, CloudWatch).
Ability to conduct performance analysis and troubleshoot large scale distributed systems.
Should be highly proactive with a keen focus on improving uptime/availability of our mission critical services.
Strong expertise in troubleshooting complex production issues.
Excellent problem solving, critical thinking, and communication skills.
Proven ability to resolve incidents, perform root cause analysis, and drive system reliability improvements.
Experience using GenAI or automation tools for issue detection, alerting, or remediation.
Experience in data visualization tools such as Tableau, Business Objects, ThoughtSpot.

Minimum Qualifications

4+ years experience in cloud-native services, including ETL frameworks like Apache Spark, and Flink.
4+ years experience in messaging systems (Kafka) and cloud infrastructure & services, AWS, GCP, Kubernetes.
4+ years of experience in modern & distributed databases such as Snowflake, Cassandra, SingleStore, and SAP HANA.
4+ years of programming experience in Python or Java.
BS/MS in computer science or equivalent experience.