Build Engineer - Bazel - #4770

Our mission is to detect cancer early, when it can be cured. We are working to change the trajectory of cancer mortality and bring stakeholders together to adopt innovative, safe, and effective technologies that can transform cancer care.

We are a healthcare company, pioneering new technologies to advance early cancer detection. We have built a multi-disciplinary organization of scientists, engineers, and physicians and we are using the power of next-generation sequencing (NGS), population-scale clinical studies, and state-of-the-art computer science and data science to overcome one of medicine’s greatest challenges.

GRAIL is headquartered in the bay area of California, with locations in Washington, D.C., North Carolina, and the United Kingdom. It is supported by leading global investors and pharmaceutical, technology, and healthcare companies.

For more information, please visit grail.com

Responsibilities

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• 4+ years of experience working on build systems, CI/CD, or developer productivity / platform tooling.
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• 2+ years of hands-on experience with a large-scale build system (for example Bazel, Buck, Pants, Gradle, or CMake).
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• 2+ years of experience building and maintaining CI/CD pipelines in GitLab CI, GitHub Actions, Jenkins, or a comparable system.
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• 3+ years of professional coding experience in one or more of Go, Python, TypeScript, or Java.
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• 1+ years of hands-on experience with AWS and containerized workloads on Kubernetes.
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• BS in Computer Science or a related technical field, or equivalent experience.

Preferred Qualifications

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• Production Bazel experience, especially in a large, multi-language monorepo.
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• Experience with Bazel rules and toolchains, remote caching, remote execution, test sharding, or build performance optimization.
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• Experience with dependency management, hermetic and reproducible builds, and test infrastructure at scale.
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• Experience improving developer experience in a mixed-language engineering environment (Go, Python, TypeScript, Java).
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• Experience building internal CLIs, automation, release tooling, or self-service developer platforms.
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• Experience defining and using developer-productivity metrics to prioritize work and demonstrate impact.
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• Experience diagnosing and reducing CI flakiness, build nondeterminism, and long-tail pipeline failures.
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• Experience supporting scientific, research, or data-intensive teams, including Python packaging and container image workflows.
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• Strong debugging skills across complex, multi-team build, test, and pipeline failures.
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• Clear communication and collaboration skills, with a track record of working directly with developers, researchers, and platform engineers.
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• Comfortable using modern AI coding agents as part of day-to-day engineering work while applying sound engineering judgment.
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• Experience mentoring engineers or driving adoption of tooling and standards across teams.