Job description

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. ROLE OVERVIEW Software Infrastructure owns the CI/CD and release pipeline that every d-Matrix engineer ships through. As a Staff-level individual contributor, you will drive the automation that diagnoses and fixes pipeline failures, such as deciding whether a failed CI job is a real regression, a flaky card, or an infrastructure issue, and identifying which merge broke an overnight test run. Rapid company growth and AI-accelerated development are increasing development velocity, and the pipeline from product through dev, test, and release must keep pace. You will blend modern AI techniques with traditional software automation to build highly reliable systems, and shape the architecture for compute and storage across an environment that spans cloud to on-prem, from firmware updates to rack-scale performance testing. You will partner with the Software Infrastructure team, development groups, and Quality Engineering to develop and spread best practices across the organization. This role is not primarily an AI agent role, and it is not a DevOps role. Kubernetes and systems skills are valued but are not the focus. WHAT YOU WILL DO - Design and build automation that diagnoses and resolves CI/CD pipeline failures, including classification of regressions, flaky hardware, and infrastructure issues. - Develop automated methods to identify which merges cause failures in long-running test suites. - Evaluate and integrate AI techniques alongside deterministic automation to maximize reliability. - Architect scalable compute and storage for build and test workloads across cloud and on-prem environments. - Own release engineering practices, including versioning schemes, independent component release trains, and compatibility matrices. - Reduce developer toil and time-to-signal across the product, dev, test, and release pipeline. - Partner with development groups and Quality Engineering to drive adoption of new tooling and best practices. WHAT YOU WILL BRING - Track record of building automation that measurably reduced toil or time-to-signal in a CI, release, or dev-tooling context. - Release engineering experience, including versioning schemes, independent component release trains, and compatibility matrices. - Architectural judgment on trade-offs such as AI versus deterministic software, and compute availability versus data locality. - Strong software engineering fundamentals, with experience building production-grade automation rather than scripts. - Track record of driving adoption of new tooling and best practices across teams that do not report to you. PREFERRED QUALIFICATIONS - Experience with GitLab CI and merge-train workflows at scale. - Hands-on experience building LLM-based agents or tools for developer workflows, such as CI triage or code review. - Experience with semantic versioning or independently versioned multi-component release systems. - Experience as a user of CI/CD systems, with an understanding of the developer-customer perspective. - Hands-on experience with containerized workloads, VMs, and Kubernetes. - Experience with observability of distributed systems, including metrics, logging, reporting, and alerting. - Systems administration skills for investigating host-level issues. Equal Opportunity Employment Policy d-Matrix is proud to be an equal opportunity workplace and affirmative action employer. We’re committed to fostering an inclusive environment where everyone feels welcomed and empowered to do their best work. We hire the best talent for our teams, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status. Our focus is on hiring teammates with humble expertise, kindness, dedication and a willingness to embrace challenges and learn together every day. d-Matrix does not accept resumes or candidate submissions from external agencies. We appreciate the interest and effort of recruitment firms, but we kindly request that individual interested in opportunities with d-Matrix apply directly through our official channels. This approach allows us to streamline our hiring processes and maintain a consistent and fair evaluation of al applicants. Thank you for your understanding and cooperation.

Requirements

Must-haves

If you want to create what comes next and help make infinite inference possible, we’d love to hear from you.
This role is not primarily an AI agent role, and it is not a DevOps role. Kubernetes and systems skills are valued but are not the focus.
Design and build automation that diagnoses and resolves CI/CD pipeline failures, including classification of regressions, flaky hardware, and infrastructure issues.
Develop automated methods to identify which merges cause failures in long-running test suites.
Evaluate and integrate AI techniques alongside deterministic automation to maximize reliability.
Architect scalable compute and storage for build and test workloads across cloud and on-prem environments.
Own release engineering practices, including versioning schemes, independent component release trains, and compatibility matrices.
Reduce developer toil and time-to-signal across the product, dev, test, and release pipeline.
Partner with development groups and Quality Engineering to drive adoption of new tooling and best practices.
Track record of building automation that measurably reduced toil or time-to-signal in a CI, release, or dev-tooling context.
Release engineering experience, including versioning schemes, independent component release trains, and compatibility matrices.
Architectural judgment on trade-offs such as AI versus deterministic software, and compute availability versus data locality.
Strong software engineering fundamentals, with experience building production-grade automation rather than scripts.
Track record of driving adoption of new tooling and best practices across teams that do not report to you.

Nice-to-haves

Experience with GitLab CI and merge-train workflows at scale.
Hands-on experience building LLM-based agents or tools for developer workflows, such as CI triage or code review.
Experience with semantic versioning or independently versioned multi-component release systems.
Experience as a user of CI/CD systems, with an understanding of the developer-customer perspective.
Hands-on experience with containerized workloads, VMs, and Kubernetes.
Experience with observability of distributed systems, including metrics, logging, reporting, and alerting.
Systems administration skills for investigating host-level issues.
Equal Opportunity Employment Policy

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aici/cdkubernetesllm

Platform: ashby
Effort: quick