Developer Experience Engineer

Job Summary

We are looking for a Developer Experience Engineer 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

How we’re different

We are a fully in-person team in San Jose (Santana Row), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.