Bazel Build Engineer - DevOps for Scalable Bio Builds

GRAIL

Menlo Park (CA)

Hybrid

USD 136,000 - 180,000

Full time

14 days+

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Benefits offered by this job

Flexible work options

Competitive benefits

Job summary

GRAIL is seeking a Build Engineer to join our DevOps / Platform Engineering team. You will help build and operate the infrastructure, tooling, and developer platforms that enable rapid, safe engineering from local development through CI/CD and release.

The role emphasizes developer experience, reducing friction in multi-language workflows and improving build-system reliability across Go, Python, TypeScript, and Java. Based in Sunnyvale with flexible on-site/remote options.

Qualifications

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

Responsibilities

Own and improve build-system workflows in a Bazel-based monorepo, including build rules, test execution, dependency management, caching, and build diagnostics.
Improve CI performance, reliability, and observability, including failure diagnostics, flaky-test handling, and pipeline maintainability.
Partner with engineering and research teams to identify and remove friction in local development, builds, tests, CI, release workflows, and tooling.
Build and maintain internal tools, automation, and self-service workflows that reduce repeated manual effort for engineers.
Diagnose complex build and CI failures across Go, Python, TypeScript, and Java codebases.
Collaborate with DevOps and platform engineers on AWS and Kubernetes infrastructure where it intersects with build, test, and delivery workflows.
Establish practical standards, documentation, and reusable patterns for build systems, CI pipelines, and developer tooling.
Take accountability for ambiguous developer-productivity problems and drive them through to measurable improvements.
Use modern AI coding agents responsibly to explore unfamiliar codebases, investigate difficult failures, prototype solutions, and accelerate tooling work.