CI Systems Engineer - AI Failure Analysis

Apple's Software Developer Workflows team delivers fast, reliable CI systems that make Apple's software easier to develop and ship.

We believe that streamlined development unlocks creativity, innovation, and potential for developers.

We're looking for a skilled CI Systems Engineer to join our team and help build intelligent AI-assisted systems that enable Apple's OS engineers to understand, diagnose, and resolve build and test failures at scale.

We value diverse perspectives and unique skills.

More than specific experience, we seek an engineer passionate about building great software, applying AI thoughtfully to real problems, continuous learning, and solving complex technical challenges.

In this role, you will design and maintain infrastructure for collecting, processing, and analyzing massive volumes of CI results data - and you will integrate AI capabilities that transform how developers interact with failure information.

Your work will turn complex failure signals into actionable insights that accelerate development, using AI to summarize failures, separate genuine issues from distractions, and help engineers focus on what needs attention.

Success requires flexibility, proactivity, and thriving in a supportive environment with challenging problems.

You'll need excellent judgment for timely technical decisions, ability to collaborate effectively on design discussions, and strong technical depth to make informed tradeoffs about when and how AI can genuinely improve developer workflows.

In your role as a CI Systems Engineer, you will work at the intersection of AI and developer tools, shaping how thousands of engineers across Apple diagnose failures.

You'll have the autonomy to evaluate new AI approaches, influence infrastructure architecture, and see your work directly reduce friction in Apple's software development process.

Experience building or integrating with AI agents using the latest-available tools such as Skills, MCP Servers, Plugins, or LLM-powered tooling Proven experience integrating AI into developer workflows with measurable impact on engineering efficiency; code review, testing, debugging, triage, or productivity tooling Familiarity with machine learning techniques applied to failure correlation, anomaly detection, or pattern recognition Deep expertise in data storage, retrieval, and analysis, including experience with relational and NoSQL databases Experience building data pipelines or working with distributed data processing frameworks Background working on large-scale data systems, observability platforms, or analytics infrastructure Experience with CI/CD failure analysis, test result aggregation, or build system diagnostics, including root cause analysis, diagnostic tooling, and observability practices Knowledge of iOS or macOS internals, development environments, build agents, and testing infrastructure BS in Computer Science or equivalent professional experience 8+ years of software engineering experience, preferably 2+ years focused on CI infrastructure, data systems, or failure analysis Experience applying AI/ML or LLM-based approaches to software development workflows, tooling, or automation Proficiency in one or more languages suited to systems and data work (Swift, Scala, Python, Go, C/C++, etc.) Proven ability to work independently on complex problems and collaborate effectively on team initiatives Strong communication skills to collaborate with diverse teams and translate complex failure data into developer-friendly insights Demonstrated experience in designing or contributing to systems that handle scale, data integrity, and query performance