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Head of Supercomputing

Etched
CompanyEtched
CategoryEngineering
LocationSan Jose
RemoteOn-site (inferred)
EmploymentNot stated
LevelDirector
SalaryNot stated by the employer
Posted26 Mar 2026
Last verified3 Aug 2026
SourceEmployer ATS (ashby)
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Description
ABOUT ETCHED Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference. 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 Etched is building at-scale AI inference supercomputers powered by our chips, and the Supercomputing organization is responsible for making them real, deployable, and reliable. We are seeking a Head of Supercomputing to define and lead the architecture, software stack, and operational model for Etched’s cluster-scale AI compute systems. This leader will own the end-to-end system software and control-plane strategy — spanning orchestration, telemetry, provisioning, networking, and fleet reliability — from first silicon through production deployment. This role combines deep systems expertise with strong organizational leadership. You will build and lead a world-class team, partnering closely with ASIC, hardware, kernel, runtime, and infrastructure teams to deliver the highest-performance AI inference systems in the world. Key Responsibilities - Define and drive the technical vision and roadmap for Etched’s Supercomputing software stack, from node bring-up to multi-rack clusters - Build, scale, and lead a high-performance Supercomputing organization - Directly manage and develop 15+ engineers with a variety of experience levels - Architect and own low-level control-plane software for system bring-up, provisioning, networking, configuration, and fleet management - Define orchestration primitives for managing devices, nodes, racks, and full cluster deployments - Oversee development of system services that interface directly with firmware, drivers, kernel subsystems, and runtime layers - Establish system telemetry and observability infrastructure for customers - Own the system software lifecycle from first silicon bring-up through stable production releases - Collaborate with manufacturing and test engineering to integrate diagnostics and system software into factory environments - Define reliability targets, operational metrics, and release processes for production deployments - Recruit, mentor, and retain exceptional systems engineers and engineering leaders - Act as a senior technical voice shaping company-wide infrastructure decisions Must-Have Skills and Experience - 15+ years of experience in system software, infrastructure, or large-scale compute systems, including 5+ years leading engineering teams - Strong understanding of hardware/software interfaces such as PCIe, RDMA, memory hierarchies, interrupts, and device drivers - Experience building or operating cluster-scale systems (HPC, AI infrastructure, hyperscale compute, or custom accelerators) - Proven track record of delivering complex systems from early bring-up through production - Strong debugging skills across hardware–software interactions - Excellent leadership, communication, and cross-functional collaboration skills Benefits - Medical, dental, and vision packages with generous premium coverage - $500 per month credit for waiving medical benefits - Housing subsidy of $2k per month for those living within walking distance of the office - Relocation support for those moving to San Jose (Santana Row) - Various wellness benefits covering fitness, mental health, and more - Daily lunch + dinner in our office - Unlimited compute budget subject to ROI justification How we’re different Etched believes in the Bitter Lesson http://www.incompleteideas.net/IncIdeas/BitterLesson.html. We are the first inference-focused frontier AI system, betting early on transformer and transformer-like architectures and on increasing model sizes. Our addr