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d-Matrix

Delivers memory-integrated AI compute platforms

Director Site Reliability Engineer - AI Infrastructure

Site Reliability EngineeringConfirmed live in the last 24 hours
Full-timeSanta Clara, CA, USA$195k - $285k /yrHybrid

About the Job

Requirements

  • A bachelor's or master's degree in Computer Science, Electrical Engineering, or a related field.
  • At least 15 years of experience in site reliability engineering, infrastructure engineering, or production engineering.
  • At least 5 years leading site reliability or infrastructure engineering teams, including building or significantly rebuilding a function rather than managing a steady-state team.
  • A track record of establishing site reliability engineering as a discipline in an organization that lacked it, including defining service-level objectives, creating on-call frameworks, standing up observability, and driving cultural change with teams from a reactive operations background.
  • Deep Linux systems expertise, including bare-metal operations and enterprise shared storage such as NAS/SAN, NFS/SMB at scale, and snapshot and replication architectures, plus hybrid-cloud storage integration.
  • Experience operating colocation and on-premises hardware at scale, including server lifecycle, power and cooling awareness, and rack-level networking.
  • Hands-on production experience with Infrastructure as Code using Terraform and Ansible, including module design, remote state, environment isolation, and change governance.
  • Experience with Kubernetes cluster operations, including lifecycle management, workload reliability, storage, and RBAC at scale.
  • Experience owning an observability stack such as Prometheus, Grafana, Datadog, or Splunk for service-level objective definition, alert design, and signal quality.
  • Strong Python and/or Go skills for production services and automation that safely touches real infrastructure.
  • Ability to communicate infrastructure health and operational risk clearly to senior leadership and non-technical stakeholders.
  • Comfort operating in a high-ambiguity, low-process environment and building structure rather than inheriting it.

Responsibilities

  • Build and lead the site reliability engineering function from scratch by defining its charter, establishing the discipline across hardware and software engineering, and hiring, developing, and retaining a team of 1–3 site reliability engineers.
  • Lead the Data Center & Lab Technician team, setting priorities and operational standards across on-premises and colocation facilities.
  • 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.
  • Establish site reliability engineering processes by defining service-level indicators, service-level objectives, and error budgets; designing on-call rotations, including a follow-the-sun model as the company expands globally; and building the incident and root cause analysis framework.
  • Own the observability stack, instrumenting metrics, traces, and logs for service-level objective visibility and alert design.
  • Drive Infrastructure as Code-first automation and build self-healing infrastructure, including host lifecycle automation, fleet auto-remediation, and AIOps-driven alerting.
  • Own FinOps and capacity planning across cloud, colocation, and on-premises environments, including spend attribution, total cost of ownership modeling, and workload placement decisions.
  • Lead migration from ad-hoc JBOD storage to an enterprise-grade shared storage platform across on-premises, colocation, and cloud, including architecture, vendor selection, and disaster recovery design.

Desired Qualifications

  • Experience operating customer-facing infrastructure or platform services with reliability expectations beyond internal tooling.
  • Knowledge of high-speed interconnect fabrics such as InfiniBand, RoCE, or NVLink, including setup, troubleshooting, and performance tuning.
  • Experience with high-performance computing job schedulers such as Slurm or LSF, including setup, tuning, and integration with infrastructure automation.
  • Multi-cloud hybrid operations across AWS, Azure, and Google Cloud Platform alongside on-premises and colocation, with unified observability and Infrastructure as Code.
  • FinOps expertise, including cloud spend attribution, total cost of ownership modeling across cloud, on-premises, and colocation, and translating cost data into workload placement recommendations.
  • Familiarity with ITIL or an equivalent structured incident, problem, and change management framework.
  • Published technical writing, conference talks, or open-source contributions in reliability, observability, or high-performance computing infrastructure.

About the Company

d-Matrix

Delivers memory-integrated AI compute platforms

d-Matrix provides scalable AI compute platforms for large datacenters with a focus on energy efficiency. Its core offering, the digital in-memory compute (DIMC) engine, places compute directly in programmable memory and uses a fabric of low-power, modular chiplets plus software to optimize AI inference. It differentiates itself by combining memory-integrated computation with a modular, chiplet-based design that reduces power use and data movement for high-volume workloads. The goal is to help large datacenters run AI workloads more efficiently at scale through customizable, energy-efficient compute solutions.

Company size
201-500
Company stage
Series C
Total funding
$429M
Headquarters
Santa Clara, CA
Founded
2019

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