d-Matrix builds full-stack, in-memory compute platforms that accelerate and lower the cost of large-scale AI inference in data centers.
At d-Matrix, we are focused on unleashing the potential of generative AI to power the transformation of technology. We are at the forefront of software and hardware innovation, pushing the boundaries of what is possible. Our culture is one of respect and collaboration. We value humility and believe in direct communication. Our team is inclusive, and our differing perspectives allow for better solutions. We are seeking individuals passionate about tackling challenges and are driven by execution. Ready to come find your playground? Together, we can help shape the endless possibilities of AI. Director, Site Reliability Engineering - AI Accelerator Infrastructure - Contract About d-Matrix d-Matrix designs and manufactures purpose-built AI inference silicon. Our engineering organization spans silicon, software, hardware, QA, and research, and the infrastructure that underpins all of it must be as reliable and scalable as the chips we build. We compete directly with Nvidia for engineering talent and hold ourselves to the same bar—the infrastructure organization is no exception. The SRE team owns the physical and virtual infrastructure layer that the entire company — and our customers — depends on. This is a high-ownership, high-impact role where infrastructure is a competitive differentiator, not a commodity. The Role: 6 month contract to full-time conversion You will build and lead d-Matrix’s site reliability engineering function from the ground up—owning the infrastructure that development, validation, and customer-facing deployments run on. This spans colocation facilities, on-premises lab clusters, cloud environments (AWS, Azure, and GCP), and the platform services customers use to collaborate with d-Matrix on hardware and software deployments. You are a hands-on engineering leader. You will establish SRE as a discipline at d-Matrix; hire and grow the team; set the technical direction; own SLOs for critical systems; and be the senior escalation point when things go wrong—all in parallel. You will partner closely with the director of DevOps engineering, whose pipelines and automation run on the infrastructure you own, and work directly with hardware and software development teams to ensure HPC infrastructure meets their workload requirements. Leadership is not a function you delegate. It is the job. What You Will Do Leadership & Organizational Build-Out - Own the SRE function end-to-end: define the team’s charter, establish SRE as a discipline within d-Matrix’s engineering culture, and drive buy-in across hardware, software, and executive stakeholders who have operated without a dedicated SRE team. - Hire, develop, and retain a team of 3–5 SRE engineers; establish a culture of operational excellence, ownership, and continuous improvement from day one. - Define the SRE technical roadmap: reliability architecture, automation priorities, capacity planning, and on-call model—and execute against it with your hands on the keyboard where needed. - Serve as the senior technical escalation for critical incidents—guiding cross-team triage, driving RCA, and ensuring systemic fixes rather than point patches. - Translate operational signals and infrastructure health into clear, actionable narratives for engineering leadership and executive stakeholders. - Partner with the director of DevOps engineering to align infrastructure reliability with pipeline and automation delivery; the two functions must operate as a unified platform. - Direct a dedicated data center & lab technician team—your hands and feet across on-premises and colocation facilities; set their work priorities, establish operational standards, and ensure physical infrastructure execution aligns with the SRE technical roadmap. Reliability & Observability — Building From Scratch - Establish SRE processes from a zero baseline: define SLIs and SLOs, build error budgets, design on-call rotations, and create the incident management framework d-Matrix currently lacks. - Own 24×7 reliability across colocation, on-premises lab clusters, cloud, and customer-facing platform services — designing for failure domains, progressive delivery, and strict change control at every tier. - Own the full observability stack (metrics, traces, and logs) and instrument it from the ground up—Prometheus, Grafana, and/or Datadog—with SLO visibility, alert design, and E2E signal quality. - Evolve incident and problem management into a data-driven discipline: automated triage workflows, pattern detection across recurring failures, and every P0/P1 producing a written RCA with tracked systemic fixes. - Own FinOps and capacity planning as a unified discipline across all three infrastructure tiers—cloud (AWS, Azure, GCP), colocation, and on-premises: establish spend visibility and attribution across every tier, model TCO comparatively, drive workload placement decisions based on cost and performance, and anticipate infrastructure needs for new silicon programs and customer deployments. - Own the migration from ad hoc JBOD-based storage and point-in-time snapshots to an enterprise-grade shared storage platform spanning on-premises, colocation, and cloud tiers—covering architecture, vendor selection, data protection design (snapshots, replication, DR), and integration with HPC workloads and development environments. Automation & Infrastructure as Code — Establishing the Baseline There is no automation baseline today. You will build it. - Drive IaC-first discipline across the team—Terraform, Ansible, and production-quality automation for all infrastructure provisioning and lifecycle management; this capability is currently absent, and you will establish it. - Build self-healing infrastructure platforms: host lifecycle automation, fleet auto-remediation, and AIOps-driven alerting that reduce manual intervention across the operational lifecycle. - Instrument the team’s own development practices—runbooks, change governance, and