Etched.ai is an AI infrastructure company building rack-scale and frontier inference systems.
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 We are using AI to build and ship AI hardware. Etched’s production ramp requires thousands of interdependent, chained decisions that involve product configurations, material availability, production capacity, capital commitments, complex logistics, field deployments, customer commitments, and more. You will embed with Platform, Production, Supply Chain, Finance, and manufacturing partners to build the agentic systems that make those decisions faster and better. You will own the development of agentic systems that loop signal to execution: understanding what Etched needs to manufacture and deliver; modelling production plans and scenarios; triaging changes and the unexpected; capturing decisions in the systems we execute through - and designing agents that augment and scale our teams. Success is measured by what we deliver, the schedules we attain, our ramp speed, and time from signal to action. Production is the product. Etched offers a unique environment to tackle real supply-chain challenges and production decisions with frontier model capabilities: we have our own in-office cluster to run agentic systems on, all teams are in-person, and every cluster we deploy offers an opportunity to raise the bar across production. You will build the frontier systems that help us coordinate execution and learn from every build. Key responsibilities - Build, deploy, and operate AI systems that run S&OP, material planning, build readiness, manufacturing partner execution, quality, logistics, and customer deployments. - Embed with Platform, Production, Supply Chain, Finance, and other teams to identify high-leverage decisions, turn them into executable workflows augmented by agentic systems, and own outcomes. - Build operational models connecting demand, product configurations, revisions, BOMs, supply, inventory, cost, capacity, builds, tests, quality, and shipments. - Build agents that craft executable plans considering demand, supply, capacity, inventory, capital, schedules, and risk - and keep those plans current as constraints change. - Propagate design changes through material exposure, sourcing, cost, factory and test readiness, production schedules, and delivery commitments. - Build production and quality agents that coordinate clear-to-build, work in progress, bottlenecks, testing, excursions, genealogy, containment, root-cause analysis, and corrective action. - Design historical replays and live evals tied to operating outcomes including forecast quality, schedule attainment, inventory, cost, yield, throughput, and resolution time. - Continuously evaluate frontier models and system optimization methods. You may be a good fit if you have - A track record of solving hard problems across stacks and domains. You enjoy being dropped into unfamiliar territory and figuring it out - Comfort with Python and code: you can read it, modify it, debug it, and direct AI to write it well. We do not care whether you write code from scratch. We care whether you ship things that work - Fluency using AI to learn and ramp on new problems; agentic coding tools, deep research, and frontier models are how you work, not an add-on - Hands-on experience building and shipping LLM-based agents or AI tooling that real users depend on (beyond just calling an AP - context engineering, tool integration, orchestration, failure analysis) - An eval-driven mindset: you measure whether AI systems actually work before scaling them - High agency and comfort with ambiguity. You can find the problem, not just solve the stated one - Worked in complex hardware, manufacturing, supply chain, S&OP, operations research, or enterprise planning, ideally through periods of hyperscale Strong candidates may also have experience with - ERP/MRP, PLM, MES, and/or QMS - BOMs and ECOs, NPI and ramp, factory test, or quality systems - Forecasting, constraint optimization, simulation, or digital twins 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 and 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 addressable market is the entirety of inference, unlike many of our competitors. 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.