Software Engineer, Triage Intelligence and Debug Engineering, CoreOS

We are looking for a curious and motivated Software Engineer with a passion for OS internals, automation, and intelligent systems. The impact of this role is broad and direct — your investigations will uncover failures affecting Apple's entire device ecosystem, your contributions will touch software running across iPhone, Mac, and Apple Silicon, and the automation pipelines you help build will shape how reliability engineering scales across Apple. You will dig into the operating system to understand the true origin of crashes and panics — not just the symptom at the top of a stack trace, but the underlying system-level conditions that caused it. You will operationalize that understanding by encoding triage logic into automation pipelines, and explore how ML and AI techniques can make those pipelines smarter over time. You will collaborate across Software, Hardware, and Silicon teams to drive issues all the way to resolution. This role is a strong fit for an engineer who is eager to learn how operating systems work at a deep level, excited to build scalable automation and intelligent tooling, and motivated by seeing their work have real, measurable impact. Minimum Qualifications Working knowledge of C and/or Swift for debug tooling or system-level development Exposure to automation frameworks, CI/CD pipelines, or scalable test systems Foundational understanding of OS internals: process and thread lifecycle, virtual memory, scheduling, synchronization, and system calls Ability to read and reason through crash reports and kernel panics — backtraces, register state, and basic memory analysis Hands-on experience with debugging tools such as LLDB, GDB, or Instruments Proficiency in Python for scripting, automation, and test infrastructure Preferred Qualifications Experience applying ML or AI techniques to systems problems — crash clustering, log anomaly detection, failure classification, or intelligent alert prioritization Familiarity with LLMs or generative AI tooling in an engineering context — prompt engineering, RAG pipelines, or AI-assisted debugging workflows Prior coursework or project experience in OS internals, systems programming, or low-level debugging Familiarity with Apple platform internals: XNU kernel, Darwin subsystems, IOKit, libdispatch, or dyld Contributions to automation frameworks or developer tooling that improved engineering productivity Experience or interest in collaborating across silicon, firmware, or platform systems teams Enthusiasm for building tools and systems that empower other engineers