
Staff Build Systems Engineer
DDN: Data Intelligence Platform Built for AI
Real job — pulled straight from DDN: Data Intelligence Platform Built for AI’s careers page · Verified August 12, 2026 · No reposts.
Job description
DDN: Data Intelligence Platform Built for AI is hiring a Staff Build Systems Engineer — a full-time, based in Pune role. Apply directly on DDN: Data Intelligence Platform Built for AI's careers page below.
Staff Build Systems Engineer
Department: Top Level - By Department
Location: Pune Office
Employment Type: FullTime
DDN is seeking a Staff Build Systems Engineer to own the build, packaging, and developer build infrastructure for Infinia Software Defined Storage (SDS). The role ensures fast, reproducible builds across C/C++, Go, and web UI components and delivers reliable container and Linux package artifacts. You will support a large, distributed engineering organization working across multiple repositories, maintaining and evolving a complex multi-repo build ecosystem powered by GitHub Actions and internal runners.
Why Join Us?
This role combines systems software, developer productivity, and product delivery. You will own a complex multi-component build ecosystem and modernize it without disrupting active development or releases.
• End-to-End Ownership: Own and evolve build workflows from source checkout through compilation, packaging, publication, and installation validation. Define and modernize build architecture while maintaining and improving existing systems to ensure reliability and scalability.
• Build Modernization: Introduce maintainable, scalable build technology while preserving existing product capabilities.
• Developer Productivity: Reduce build times, improve diagnostics, and ensure consistency across developer and CI environments. Own and enhance local developer tooling, including build scripts and containerized dev environments. Lead CI/CD design and maintenance in collaboration with DevOps where needed, and drive release automation and artifact promotion workflows to streamline delivery.
Core Responsibilities:
Own the technical direction and operational reliability of the product build ecosystem in partnership with Development, QA, Release, and DevOps.
• Build Systems and Toolchains: Own C/C++, Go, and npm build workflows, including compilers, linkers, flags, dependencies, and configuration.
• Reproducible Environments: Standardize containerized and host build environments and maintain local, CI, and release branch consistency.
• Internal Build Automation: Maintain orchestration utilities for component builds, full-product builds, packaging, and deployment preparation.
• Failure Diagnosis: Resolve compiler, linker, dependency, packaging, platform, and developer-versus-CI issues.
• Artifacts and Packaging: Produce versioned container images and Debian/RPM packages; validate dependencies, installation, upgrades, and rollback.
• CI and Artifact Repositories: Integrate builds with CI platforms and repositories such as Nexus, JFrog Artifactory, Harbor, or Quay.
• Build Performance: Improve clean and incremental build times through caching, parallelism, dependency tracking, and measurement.
What You’ll Work On:
• Build-System Modernization: Inventory SCons logic and evaluate CMake, Meson/Ninja, Bazel, and other suitable alternatives.
• Prototyping and Migration: Benchmark alternatives and deliver staged migration with compatibility, validation, and rollback plans.
• Multi-Platform Delivery: Support multiple processor architectures, Linux distributions, build variants, and release branches.
• Technical Leadership: Write designs, set standards, review changes, mentor engineers, and drive cross-team decisions.
Required Skills:
All of the following skills are mandatory:
• Experience: 8+ years in software, build engineering, developer infrastructure, or a closely related field.
• C/C++ Builds: Strong Linux compilation and linking knowledge with GCC/Clang and SCons, Make, CMake, Meson, Ninja, or Bazel.
• Automation: Strong Python and Bash skills for maintainable build tooling and diagnostics.
• Other Ecosystems: Practical experience with Go build tooling and Node.js/npm workflows.
• Containers: Experience with Docker-based build environments and multi-stage images.
• Linux Packaging: Hands-on Debian and RPM packaging, dependency management, versioning, installation, upgrades, and publication.
• CI/CD: Build-system integration with GitHub Actions, Jenkins, GitLab CI, or equivalent platforms and artifact repositories.
• Collaboration: Strong troubleshooting, documentation, communication, ownership, and cross-team technical leadership. Preferred Skills: The following skills are desirable but not mandatory: DDN Confidential
• Build Acceleration: ccache, sccache, distributed builds, remote execution, or comparable optimization technologies.
• Secure Builds: Hermetic builds, dependency pinning, provenance, SBOMs, signing, or software supply chain security.
• Migration Experience: Migration from a legacy build system to CMake, Meson/Ninja, Bazel, or a comparable platform.
• Systems Software: Storage, networking, operating system, compiler, or other performance-critical software.
• Developer Productivity: Build-health metrics, engineering standards, documentation, and self-service developer workflows.
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Frequently asked questions
What skills are required for Staff Build Systems Engineer at DDN: Data Intelligence Platform Built for AI?
The required skills for Staff Build Systems Engineer at DDN: Data Intelligence Platform Built for AI include: C++, Go, Python, Bash, Docker, GitHub Actions, Jenkins, GitLab CI, Node.js.
What is the seniority level for Staff Build Systems Engineer at DDN: Data Intelligence Platform Built for AI?
Staff Build Systems Engineer at DDN: Data Intelligence Platform Built for AI is a Staff level position.
How do I apply for Staff Build Systems Engineer at DDN: Data Intelligence Platform Built for AI?
You can view the full description and apply for Staff Build Systems Engineer at DDN: Data Intelligence Platform Built for AI on EchoJobs: https://echojobs.io/job/ddn-data-intelligence-platform-built-for-ai-staff-build-systems-engineer-kbait.