Job SummaryWe are looking for a Developer Experience Enginee
r to enhance developer productivity, automation, and infrastructure across our hardware and software teams. You will work at the intersection of DevOps, software engineering, and high-performance computing (HPC), building systems that accelerate chip design, simulation, and AI model deployment in a cloud and on-prem hybrid environment.
Key responsibilities- Develop and maintain automation tools to streamline development, testing, and deployment workflows.
- Optimize and manage Slurm-based job scheduling for AI workloads, simulation, and chip design workflows.
- Build observability solutions using Grafana, Prometheus, and OpenTelemetry for monitoring pipelines, infrastructure, and compute clusters.
- Manage and optimize containerized environments using Docker and Kubernetes to enhance scalability and reproducibility.
- Enhance build, test, and deployment pipelines with CI/CD tools like GitHub Actions, Jenkins, Buildkite, or Bazel.
- Develop caching and artifact management systems to reduce build times and improve dependency resolution.
- Integrate and manage cloud resources (AWS, GCP) for scaling compute, storage, and hybrid workloads.
- Support security and compliance efforts including secrets management and access control.
- Document and share best practices for efficient developer tooling and workflows.
You may be a good fit if you have- Strong Python skills for automation, scripting, and infrastructure development.
- Experience with Slurm job scheduling in an HPC or hybrid environment.
- Hands-on experience with observability and monitoring tools like Prometheus, Grafana, and OpenTelemetry.
- Expertise with Docker and Kubernetes, including Helm charts and cluster management.
- Proficiency in modern CI/CD pipeline management with tools like GitHub Actions, Jenkins, or Buildkite.
- Experience with infrastructure-as-code tools like Terraform or Ansible.
- Knowledge of cloud infrastructure, compute, and storage optimization on AWS or GCP.
Strong candidates may also have experience with- Data pipelining for AI/ML workflows using Airflow, Prefect, or Dagster.
- Build system expertise with Bazel, CMake, or distributed build systems.
- Secrets management tools such as Vault, SOPS, AWS Secrets Manager, or GCP Secret Manager.
- AI/ML model training workflows and monitoring GPU-accelerated workloads.
- Exposure to FPGA or ASIC development environments and workflows.
Benefits- Full medical, dental, and vision packages, with generous premium coverage
- Housing subsidy of $2,500/month for those living within walking distance of the office
- Daily lunch and dinner in our office
- Relocation support for those moving to West San Jose
- Unlimited compute budget subject to ROI justification
