Infrastructure Software Engineer (Taiwan)
About Etched
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.
Job Summary
Building cutting-edge model-specific ASICs requires crafting custom infrastructure and toolchains to support ultra-fast, reliable, and scalable development across the stack - from simulation to silicon, and manufacturing and testing from components to pods of cabinets. We build this infrastructure as software - and we engineer it with the same best practices we apply to our products. We use the same rigor, design discipline, and quality standards and testing as we do to our ASIC, software, and platform.
You will lead the development, manufacturing, and adoption of next-generation infrastructure tooling, enabling Etched ASIC, Software, and Platform engineers to iterate faster, build more reliably, manufacture with precision, and push the boundaries of AI performance. This includes building and scaling our hybrid high-performance compute (HPC) cluster, optimized for massively parallel CI, EDA workflows, Emulation, and hardware-aware job execution.
You’ll also architect and implement a state-of-the-art observability stack with LLM integration and a strong emphasis on streaming health and performance telemetry, log aggregation, distributed tracing, insight generation, synthetic testing, and smart alerting - across CI pipelines, simulation clusters, and service endpoints.
This role demands a strong software engineering mindset, quality instincts, and deep understanding of systems. It’s not just about writing scripts - it’s about writing code that builds and manages infrastructure with precision, repeatability, and intent.
Key responsibilities
Architect and Scale Distributed Compute Systems: Design and build the orchestration layers that drive our hybrid high-performance clusters—enabling simulation, synthesis, and continuous integration of AI ASICs at unprecedented scale.
Build Infrastructure-as-Code Systems: Develop and maintain a fully programmable infrastructure control plane to ensure reproducibility, auditability, and rapid iteration across the entire stack.
Optimize End-to-End Developer Experience: Create tools and abstractions that empower engineers to harness massive parallelism without worrying about the underlying complexity..
Workload Elasticity, Reliability, and Efficiency: Prototype and execute workload orchestration and migration strategies between on-premise and cloud environments, balancing performance, storage availability and replication, uptime, and cost across heterogeneous hardware and compute backends.
Implement real-time telemetry, tracing systems that surface insights from millions of metrics, enabling proactive debugging and system optimization.
Push the Limits of Observability: Build a full observability stack that includes dashboards, alerting, automated responses, and a synthetic testing framework to proactively test infrastructure performance and reliability for various application and data flows, ensuring we remain ahead of issues impacting development and productivity workflows.
Build an integrated, world-class manufacturing infrastructure: in close collaboration with partners to design, test, and ship the highest-quality AI acceleration hardware
Representative projects
Design and deploy a fully automated, scalable hybrid HPC cluster, combining bare-metal servers and switches with cloud instances, provisioned through MaaS and orchestrated via SLURM and Kubernetes, optimized for mixed EDA workloads and parallel CI pipelines.
Develop a real-time observability system for ASIC toolchain jobs and distributed builds, integrating Prometheus, Grafana, and VictoriaMetrics with streaming telemetry, tracing, and alerting to detect performance regressions before they hit silicon.
Architect and implement a programmable infrastructure-as-code control plane, using Terraform, Ansible, and Puppet, to version, audit, and redeploy every layer of Etched's 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 via a secure zero-trust network, abstracting away cluster state and machine failures.
Prototype and evaluate dynamic workload migration strategies between on-premise and cloud environments to optimize for latency, reliability, and cost across simulation and synthesis pipelines.
Design a synthetic testing and fault injection framework to validate the behavior of infrastructure under high-load, degraded hardware, and intermittent network partitions - before they happen in production.
Build manufacturing infrastructure allowing our manufacturing partners to easily, securely and reliably build, test, and capture results.
You may be a good fit if you
Are a systems-minded software engineer who loves building foundational platforms, working close to the metal and cloud, solving high-leverage problems at scale.
Are a deeply technical engineer who treats infrastructure as a software problem - prioritizing clean abstractions, version control,small change lists, easy roll backs, testing, and long-term maintainability over ad hoc configuration.
Have strong programming skills in languages such as Python, Go, Rust, and C++, and are comfortable building production-grade tooling.
Have experience manufacturing hardware working with big name firms in Taiwan
Possess expert-level knowledge of Linux, virtualization, containerization, and CI/CD pipelines, with a deep understanding of how to debug, optimize, and scale complex systems.
Are familiar with Infrastructure as Code tools like OpenTofu, Ansible, or Puppet, and enjoy designing declarative, reproducible infrastructure systems.
Understand and use PromQL and other telemetry/query languages and have used LLM to extract insight from real-time metrics, and know how to architect and tune observability stacks.
Have a track record of debugging and resolving difficult hardware-software integration problems across bare-metal systems, networks, and distributed workloads.
Can lead and mentor technical teams, guiding design decisions and helping others develop sound engineering instincts.
Have 4+ years of experience in infrastructure engineering, systems programming, or backend software development - ideally in environments where performance, scale, or hardware interaction mattered.
Are driven by curiosity, take initiative, and have an innate sense of ownership — you thrive in uncharted territory, design for edge cases, and love making systems more powerful, reliable, and elegant.
Strong candidates may also have experience with (Nice-to-have qualifications)
Familiarity with Bazel build system
Deep understanding of ASIC development flows, especially those involving Synopsys, Cadence, and Verilator, including how EDA tools interact with infrastructure for simulation, synthesis, and verification.
Hands-on experience architecting systems with AWS, GCP, or Azure, including hybrid on-prem/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.
Comfortable in profiling and optimizing compute environments for single-threaded latency, memory-bound workloads, or I/O throughput, especially in the context of simulation or CI 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 mediums (SMS, email, push alerts, etc.)
Benefits
Competitive compensation packages including generous equity packages
Comprehensive insurance coverage and other top-of-market benefits
How we’re different
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 and Taipei, 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.