Senior Infrastructure Engineer

Join d-Matrix and help build the future of AI inference. We’ve pioneered a memory-centric architecture that brings compute directly into memory, making AI faster, more energy efficient, and accessible on a global scale. From chips and software to rack-scale systems, our team is tackling some of AI infrastructure’s hardest challenges — and shipping breakthrough technology today. If you want to create what comes next and help make infinite inference possible, we’d love to hear from you.

Our culture is built on respect, collaboration, and direct communication. We value humility, we believe our different perspectives lead to better solutions, and we’re looking for people who are driven by execution and energized by hard problems.

Senior Infrastructure Engineer

Location: Remote, United States

Role Overview

Software Infrastructure runs the Kubernetes clusters, CI/CD systems, and compute environments that every d-Matrix engineer builds and tests on, along with the systems behind our externally accessible product demos. As a senior infrastructure engineer, you will be the team’s first responder and own issues end to end: diagnosing them, fixing them, and engaging IT or the product software group when the root cause sits with them. Our environment combines cloud resources, conventional servers, and our own AI accelerators and networking hardware, so quickly isolating the cause is central to the job. When an issue recurs, you will turn it into automation, better alerting, or a runbook. This is not an IT support or ticket-queue role, and IT owns physical hardware; we manage everything from the operating system up. On-call participation is expected.

Responsibilities

Own first response and resolution for issues across Kubernetes clusters, GitLab and CI runners, VMs, standalone systems, and demo environments; Triage across teams with IT and the product software group when the root cause sits on their side; Convert recurring issues into automation, alerts, and runbooks so repeat incidents decline; Improve monitoring and alerting to reduce false alarms and speed detection of real problems; Perform routine operational work, including upgrades, patching, certificate renewals, and capacity checks; Ship automation and improvements the team relies on, beyond individual fixes; Participate in on-call coverage for the environment; Contribute to design and build work across the team’s systems as your scope grows

Requirements

2+ years operating production Linux systems, including hands-on Kubernetes troubleshooting; Methodical debugging skills: forming hypotheses, narrowing them quickly, and working across layers when the obvious answer is wrong; Scripting experience in Python and/or Bash; Familiarity with CI/CD systems (GitLab preferred); Working knowledge of networking fundamentals, including DNS, routing, load balancing, and TLS; Experience with monitoring and observability tools; Clear communication under pressure, including concise incident status updates; Drive and curiosity to learn unfamiliar systems and how state-of-the-art inference systems are built

Nice to have

Experience with GPU or accelerator nodes in Kubernetes; Experience with infrastructure-as-code tools such as Ansible or Terraform; Experience with monitoring platforms such as DataDog, Prometheus, or Grafana; Bare metal or on-prem infrastructure experience; CKA or CKAD certification