About The Position

Our team is on a mission to build innovative infrastructure and tools to help other engineers be more productive and make software easier to create, build and distribute. We believe that streamlining software engineering is an important part of unlocking developer creativity and innovation, and we love it when Apple customers see that in the products we ship. We are looking for technically hands-on engineers who want to ship high-performance distributed systems that solve real-world problems at Apple scale. You would join a team of engineers who build innovative storage and backend service while tackling interesting challenges in a supportive, balanced environment. We spend most of our time building software and automation, but equally important is the work we do collaborating with teams across Apple, understanding their operational challenges, and iterating on scalable, long-term solutions together.

Requirements

  • 5+ years of professional software engineering experience
  • Experience with high-performance, strongly typed languages such as Go, Rust, Scala, or others.
  • Experience with building and operating distributed systems.
  • Familiarity with some large infrastructure systems like Kubernetes.
  • Strong interest in distributed storage, observability, reliability, and cloud services.
  • Interest in working across different levels of the stack, including debugging OS-level issues such as memory and concurrency problems.
  • Ability to efficiently develop, debug, and support new technologies in a changing environment.

Nice To Haves

  • Familiarity with application and service monitoring tools and techniques.
  • Experience with incident management and response.
  • BS in Computer Science or equivalent, related experience.

Responsibilities

  • Engineer distributed services, tooling, and operational standards
  • Collaborate with teams to refine requirements and implement lasting solutions
  • Drive service scalability, resiliency, and performance
  • Take ownership over components critical to Apple's success
  • Optimize system performance through algorithm design and testing
  • Scale services to ever-increasing problem sizes
  • Improve service operability using metrics and log data
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