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Contract Lead, Site Reliability Engineering — AI Accelerator Infrastructure

Job Overview

Location

Santa Clara

Job Type

Full-time

Category

Engineering

Date Posted

July 14, 2026

Full Job Description

📋 Description

  • 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.
  • The Contract Lead, Site Reliability Engineering (SRE) role is a 6-month contract to full-time conversion position.
  • 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.
  • 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
  • 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 deployment pipelines for infrastructure code—establishing standards that scale as the team grows.
  • Documentation & Global Collaboration
  • Build a documentation culture from scratch: runbooks, architecture diagrams, and operational playbooks maintained as living artifacts—not a one-time project.
  • Design and scale a follow-the-sun on-call model as d-Matrix expands globally; the framework you build now will be the foundation the team inherits.
  • Drive POC and POV evaluations for new infrastructure technologies, interconnect fabrics, and platform services relevant to d-Matrix’s accelerator roadmap.
  • What You Will Bring
  • Required
  • Bachelor’s or Master’s in Computer Science, Electrical Engineering, or a related field; 15+ years in SRE, infrastructure engineering, or production engineering.
  • 5+ years leading SRE or infrastructure engineering teams — including experience building or significantly rebuilding a function, not just managing a steady-state team.
  • Demonstrated track record of establishing SRE as a discipline in an organization that lacked it: defining SLOs, creating on-call frameworks, standing up observability, and driving cultural change with engineering teams that came from a reactive ops background.
  • Deep Linux systems expertise: networking (TCP/IP, RDMA, and bonding), kernel tuning, and bare-metal operations; hands-on experience with enterprise shared storage platforms (NAS/SAN, NFS/SMB at scale, and snapshot and replication architectures) and hybrid-cloud storage integration across on-prem and cloud tiers.
  • Proven experience operating colocation and on-premises hardware at scale: server lifecycle, power and cooling awareness, rack-level networking.
  • IaC fluency: Terraform and Ansible at production scale — module design, remote state, environment isolation, and change governance.
  • Kubernetes cluster operations: lifecycle management, workload reliability, storage, and RBAC at scale.
  • Full observability stack ownership: Prometheus, Grafana, and/or Datadog — SLO definition, alert design, and E2E signal quality.
  • Strong Python and/or Go — production services, not just scripts; automation that touches real infrastructure safely.
  • Executive communication: translating infrastructure health and operational risk into clear narratives for senior leadership, including stakeholders with no infrastructure background.
  • Ability to operate in a high-ambiguity, low-process environment — you build the structure, you don’t inherit it.
  • Strongly Preferred
  • Experience operating customer-facing infrastructure or platform services—reliability expectations beyond internal tooling.
  • Knowledge of high-speed interconnect fabrics: InfiniBand, RoCE, or NVLink — setup, troubleshooting, and performance tuning.
  • HPC job scheduler experience: Slurm, LSF, or equivalent — setup, tuning, and integration with infrastructure automation.
  • Multi-cloud hybrid operations: AWS, Azure, and GCP alongside on-prem/colo—unified observability and IaC across all tiers.
  • FinOps: cloud spend attribution, TCO modeling across cloud vs. on-prem vs. colo, and translating cost data into workload placement recommendations.
  • ITIL knowledge or equivalent structured incident/problem/change management framework.
  • Published technical writing, conference talks, or open-source contributions in reliability, observability, or HPC infrastructure.
  • 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 all applicants.
  • Thank you for your understanding and cooperation.

Skills & Technologies

Python
Go
AWS
Azure
GCP
DevOps
Senior
Remote
Degree Required

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About d-Matrix Corporation

d-Matrix designs silicon for high-efficiency AI inference at scale. Its Corsair compute platform combines in-memory computing with a digital approach to slash latency and energy use in transformer and generative workloads. Targeting hyperscale data centers and edge deployments, the company offers hardware and software stacks that integrate into existing AI pipelines. Founded in 2019 and headquartered in Santa Clara, California, d-Matrix serves cloud and enterprise customers seeking cost-effective alternatives to GPUs for large language model serving.

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