Developer Experience Engineer

Etched is building the world’s first AI inference system purpose-built for transformers - delivering over 10x higher performance and dramatically lower cost and latency than a B200. With Etched ASICs, you can build products that would be impossible with GPUs, like real-time video generation models and extremely deep & parallel chain-of-thought reasoning agents. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history.

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.

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  Develop and maintain automation tools to streamline development, testing, and deployment workflows.

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  Optimize and manage Slurm-based job scheduling for AI workloads, simulation, and chip design workflows.

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  Build observability solutions using Grafana, Prometheus, and OpenTelemetry for monitoring pipelines, infrastructure, and compute clusters.

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  Manage and optimize containerized environments using Docker and Kubernetes to enhance scalability and reproducibility.

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  Enhance build, test, and deployment pipelines with CI/CD tools like GitHub Actions, Jenkins, Buildkite, or Bazel.

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  Develop caching and artifact management systems to reduce build times and improve dependency resolution.

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  Integrate and manage cloud resources (AWS, GCP) for scaling compute, storage, and hybrid workloads.

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  Support security and compliance efforts including secrets management and access control.

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  Document and share best practices for efficient developer tooling and workflows.

• 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.

• 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.

Etched believes in the Bitter Lesson. We think most of the progress in the AI field has come from using more FLOPs to train and run models, and the best way to get more FLOPs is to build model-specific hardware. Larger and larger training runs encourage companies to consolidate around fewer model architectures, which creates a market for single-model ASICs.

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 as needed.