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Etched

Designs chips and servers for running AI models

Infrastructure Software Engineer

Platform EngineeringConfirmed live in the last 24 hours
Full-timeSan Jose, CA, USA

About the Job

Requirements

  • Strong programming skills in languages such as Python, Go, Rust, and C++, and ability to build production-grade tooling.
  • Expert-level knowledge of Linux, virtualization, containerization, and continuous integration and continuous delivery pipelines, including debugging, optimizing, and scaling complex systems.
  • Familiarity with infrastructure-as-code tools such as OpenTofu, Ansible, or Puppet, and ability to design declarative, reproducible infrastructure systems.
  • Understanding and use of PromQL and other telemetry/query languages; experience using large language models to extract insight from real-time metrics; and knowledge of architecting and tuning observability stacks.
  • Track record of debugging and resolving difficult hardware-software integration problems across bare-metal systems, networks, and distributed workloads.
  • Ability to lead and mentor technical teams, guide design decisions, and help others develop sound engineering instincts.
  • At least 8 years of experience in infrastructure engineering, systems programming, or backend software development, ideally in environments where performance, scale, or hardware interaction mattered.

Responsibilities

  • Design and build orchestration layers for hybrid high-performance clusters that enable simulation, synthesis, and continuous integration of AI application-specific integrated circuits at scale.
  • Develop and maintain a programmable infrastructure control plane to ensure reproducibility, auditability, and rapid iteration across the stack.
  • Create tools and abstractions that enable engineers to use massive parallelism without managing the underlying complexity.
  • Prototype and execute workload orchestration and migration strategies between on-premises and cloud environments, balancing performance, storage availability and replication, uptime, and cost across heterogeneous hardware and compute backends.
  • Implement real-time telemetry and tracing systems that surface insights from millions of metrics to enable proactive debugging and system optimization.
  • Build an observability stack with dashboards, alerting, automated responses, and synthetic testing to proactively assess infrastructure performance and reliability across application and data flows.
  • Design and deploy an automated, scalable hybrid high-performance computing cluster combining bare-metal servers and switches with cloud instances, provisioned through MaaS and orchestrated with SLURM and Kubernetes for mixed electronic design automation workloads and parallel continuous-integration pipelines.
  • Develop a real-time observability system for application-specific integrated circuit toolchain jobs and distributed builds, integrating Prometheus, Grafana, and VictoriaMetrics with streaming telemetry, tracing, and alerting to detect performance regressions.
  • Architect and implement an infrastructure-as-code control plane using Terraform, Ansible, and Puppet to version, audit, and redeploy the development stack with deterministic reproducibility.
  • Create a zero-downtime interactive development environment that provisions and connects Jupyter and VS Code sessions to GPUs and high-memory nodes through a secure zero-trust network, abstracting cluster state and machine failures.
  • Prototype and evaluate dynamic workload migration strategies between on-premises and cloud environments to optimize latency, reliability, and cost across simulation and synthesis pipelines.
  • Design a synthetic testing and fault-injection framework to validate infrastructure behavior under high load, degraded hardware, and intermittent network partitions before production.

Desired Qualifications

  • Familiarity with the Bazel build system.
  • Deep understanding of application-specific integrated circuit development flows, especially Synopsys, Cadence, and Verilator, including how electronic design automation tools interact with infrastructure for simulation, synthesis, and verification.
  • Hands-on experience architecting systems with AWS, GCP, or Azure, including hybrid on-premises/cloud deployments, workload migration strategies, and cloud-native orchestration tooling.
  • Experience monitoring, provisioning, and debugging bare-metal servers, network hardware, and high-performance storage systems in rack-scale environments.
  • Experience profiling and optimizing compute environments for single-threaded latency, memory-bound workloads, or input/output throughput, particularly for simulation or continuous-integration performance.
  • Proficiency building or operating telemetry systems at scale using Prometheus, Grafana, Loki, VictoriaMetrics, and tools for distributed tracing, log aggregation, and real-time alerting across heterogeneous channels such as SMS, email, and push alerts.

About the Company

Etched

Designs chips and servers for running AI models

Etched designs AI chips and the server racks built around them for AI companies and cloud providers, focusing only on inference, the work of running trained models to answer requests. In 2024, it unveiled a chip hard-wired to run only transformers, the type of AI model behind ChatGPT, after betting at its founding that they would dominate AI. Etched develops its chips, racks, and software together, and each rack links many chips through a shared pool of fast memory so very large models with long inputs can answer quickly. It earns money by selling these complete systems rather than individual chips. Etched was founded in 2022 and is based in San Jose, California.

Company size
201-500
Company stage
Series D
Total funding
$1.6B
Headquarters
San Jose, CA
Founded
2022

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