Apple
Principal Engineer, Apple Cloud Object Storage (ACOS), Storage Infrastructure
$205K–$374K
Seattle, Washington · Principal · Full-time · Posted Sep 14, 2026
- Experience
- 15+ years in software development, including 10+ years designing, building, and operating large-scale distributed storage systems.
- Education
- BS, MS, or PhD in Computer Science or a related field.
About the job
Leads the technical strategy and operation of Apple’s exabyte-scale object storage data path, improving its efficiency, integrity, performance, and capacity management.
What you'll do
- Own the multi-year architecture and roadmap for encoding, placing, and serving ACOS data; identify and prioritize key technical problems.
- Lead storage efficiency, integrity, performance, and capacity initiatives, including encoding, repair, tiering, and hardware-generation transitions.
- Lead high-consequence system design, mentor senior engineers, and align stakeholders across engineering, hardware, operations, and customers.
What they ask for
- 15+ years in software development, including 10+ years designing, building, and operating large-scale distributed storage systems.
- Proven delivery of storage systems at ~exabyte scale, with depth in encoding, replication, placement, repair, consistency, and consensus.
- Hands-on expertise in Reed-Solomon, Local Reconstruction Codes, wide-stripe and geo-distributed coding, and quantitative durability, availability, repair-bandwidth, and IOPS trade-offs.
- Experience with modern drive architectures and high-performance storage workloads, plus operational experience carrying a pager for a large-scale storage system.
Nice to have
- PhD in distributed systems or storage.
- Experience building a funded, multi-year plan to lower cost per usable byte; production durability guarantees, performance tiers for AI/ML and data teams, or demand-aligned capacity.
Pay
$205,400 and $374,300 USD base salary
Tools
Reed-Solomon, Local Reconstruction Codes, Paxos, Raft, Google Colossus, Ceph/RADOS, Azure Blob Storage, Amazon S3
AI focus
Support high-performance SSD-backed storage tiers for data and AI workloads; account for AI/ML workload I/O patterns, including training pipelines.
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