Staff Software Engineer (Libraries)

About the Role

Join Chainguard's Libraries team as a Staff Software Engineer to drive the technical strategy and implementation for our secure, reliable, and automated build systems, with a special focus on AI/ML toolchain packages. Your expertise will expand Chainguard’s coverage over mission-critical libraries and improve vulnerability remediation workflows.

Responsibilities

• Design, build, and maintain AI/ML package infrastructure, including building, testing, and distributing ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) in reproducible and secure ways.
• Develop and maintain Terraform modules and infrastructure-as-code (IaC) patterns to support reproducible deployment of ML services and pipelines.
• Contribute to automation pipelines for building and verifying AI/ML packages (Python wheels, containers, etc.).
• Assist with troubleshooting toolchain-related build failures.
• Implement and maintain observability, CI/CD, and policy enforcement systems for AI/ML workloads and infrastructure.
• Evaluate and integrate emerging technologies in the AI/ML ecosystem with secure-by-default packaging and reproducibility principles.

Requirements

• Familiarity with Terraform, Kubernetes, and cloud infrastructure (GCP, AWS, or Azure).
• Experience in Python packaging, including building and distributing wheels and dependencies.
• Background in compilers, toolchains, and native build systems.
• Experience with ML frameworks (e.g., TensorFlow, PyTorch, JAX) and their build/deployment ecosystems.
• Familiarity with software supply chain security best practices (SLSA, SBOMs, sigstore, etc.).
• Experience with CI/CD and automation tools (e.g., GitHub Actions, Argo Workflows, Tekton, or similar).

Nice-to-Haves

• Working knowledge of Linux packaging and reproducible build systems (Alpine, Wolfi, Nix, Bazel, etc.).
• Contributions to open-source ML, DevOps, or packaging projects.
• Experience with secure software supply chain tooling (SBOMs, provenance, attestation).
• Understanding of AI/ML infrastructure orchestration tools (Kubeflow, MLflow, Vertex AI, SageMaker, etc.)