Atomic Machines is building the Matter Compiler™, the first in a new class of AI-native, all-digital manufacturing systems that build working machines directly from code. The Matter Compiler (MC) is aimed at micro-machines: motors and gears the size of a grain of sand, robots small enough to work inside the body, cooling built directly into the chips that run AI, and the many devices like them that have been waiting on a way to build them. Its first product is PrimeSwitch™, an electromechanical power relay the size of a button battery that carries 150 amps continuous current and opens in 50 microseconds, about a thousand times faster than a conventional contactor. Founded by Jeff Holden — serial entrepreneur, ex-Amazon SVP and Uber’s first Chief Product Officer — the company has raised $250 million to date.
Atomic Machines is based in the San Francisco Bay Area, with offices in Emeryville and Santa Clara.
The Matter Compiler runs on a fleet of nodes that control real-world equipment. Every build, release, and deployment that reaches that fleet goes through infrastructure this role owns: the build system for a multi-package monorepo that ships to several architectures, the CI/CD pipeline from push to green, the artifact store and shared cache, and the path that deploys software to about 80 nodes today and thousands of devices across several metros by 2027.
You will own this infrastructure end to end: design, build, operate, and improve. You will decide what gets automated and what stays manual. You will set the blast-radius limits that stop a bad build from reaching the whole fleet. You will define the signals that tell us CI is degrading before engineers notice. And you will make the engineers around you change how they work, because at Staff, adoption is the job.Hardware experience is not required. What this role needs is the ability to decompose ambiguous system failures, reason across abstraction layers, and own problems that cross team and org boundaries.
- Own the build system for a 40-package monorepo that targets three architectures: hermetic builds, honest lockfiles, change detection, and a shared remote cache keyed on real inputs.
- Own CI/CD end to end, including rollback. Measure push-to-green, queue depth, and fetch error rate. Drive the numbers down and show the result.
- Design and operate the fleet deployment path: immutable artifacts, staged rollout, version handshake, drift detection, and an abort path that does not depend on the deploy script.
- Define the production signals and thresholds for pipeline health, and the runbook an on-call engineer can run without you. Turn runbook steps into pipeline checks and auto-remediation where it pays back.
- Own build-runner security as a blast-radius problem: short-lived credentials, scoped IAM, rotation as a mechanism, secret scanning in CI.
- Work with IT on the GitLab, network, and identity boundaries. Ask where the boundary is instead of assuming it.
- Remove toil with a number attached: what engineers did by hand before, how often, and what they do by hand now.
- Drive adoption across teams that do not report to you. Make the new way the default and the old way slower.
- Raise reliability standards without blocking delivery. Encode what you learn from incidents into systems, not reminders.
- Ownership of a build system for a repository with many packages and more than one build target, including what was wrong with it and what you changed.
- Ownership of a CI/CD system end to end, including rollback, with an opinion on what made deployments safer over time.
- Deep fundamentals in build reproducibility and caching: why a test passes locally and fails in CI, what belongs in a cache key, and how a correct key can still serve a wrong artifact.
- Deep fundamentals in fleet deployment: why mutable tags cause drift, how to deploy by digest, and how a node that has been offline rejoins production safely.
- Experience designing failure paths that are concrete: what times out, what safe state is left behind, and what the next engineer sees.
- A record of production incidents you diagnosed to root cause, with a mechanism, a measurement, and a fix.
- A record of getting other engineers to adopt infrastructure you built, and the lever you used.
- Candor about what you are not good at, and ownership of outcomes, including the ones that went wrong.
- Fluency with AI tools in your daily engineering work, while owning the decisions, code, and results you accept.
- Ability to work onsite five days per week
- Experience deploying software to distributed nodes that control physical equipment.
- Experience with GitLab CI, Ansible, OIDC/STS-based credential flows, and artifact stores at scale.
- Experience operating infrastructure through a growth phase from tens to thousands of endpoints.
The compensation for this position also includes equity and benefits.
Atomic Machines is an equal opportunity employer that values diversity and does not discriminate based on characteristics protected by applicable law. We are committed to an inclusive interview experience, including for individuals with disabilities. To request an accommodation, contact [email protected]. To help our recruiting team manage application volume and respond to candidates more efficiently, Atomic Machines may use AI-assisted tools.
Atomic Machines Berkeley, California, USA Office
950 Gilman Street , Suite 800, , Berkeley, CA, United States, 94710
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