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Director Site Reliability Engineer, AI Infrastructure
D Matrix
Santa Clara, USA
Full-time
Director
Hybrid
Discovered 4 weeks ago
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Key Skills for This Role
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What You Will Do
- Build and lead the SRE function from scratch — define its charter, establish SRE as a discipline across hardware and software engineering, and hire, develop, and retain a team of 1–3 SRE engineers.
- Direct a dedicated Data Center & Lab Technician team, setting work 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 SRE process from zero: define SLIs/SLOs and error budgets, design on-call rotations (including a follow-the-sun model as d-Matrix expands globally), and build the incident and RCA management framework.
- Own the full observability stack (Prometheus, Grafana, Datadog, Splunk or equivalent), instrumenting metrics, traces, and logs for SLO visibility and alert design.
- Drive IaC-first automation (Terraform, Ansible) and build self-healing infrastructure — host lifecycle automation, fleet auto-remediation, and AIOps-driven alerting.
- Own FinOps and capacity planning across cloud, colocation, and on-premises tiers, including spend attribution, TCO modeling, and workload placement decisions.
- Lead the migration from ad-hoc JBOD storage to an enterprise-grade shared storage platform spanning on-prem, colocation, and cloud, including architecture, vendor selection, and DR design.
- What You Will Bring
- 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 teams coming from a reactive ops background.
- Deep Linux systems expertise: bare-metal operations, enterprise shared storage platforms (NAS/SAN, NFS/SMB at scale, snapshot and replication architectures), and hybrid-cloud storage integration.
- Proven experience operating colocation and on-premises hardware at scale: server lifecycle, power and cooling awareness, rack-level networking.
- Hands-on Infrastructure as Code fluency with 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, Datadog and/or Splunk or equivalent) for SLO definition, alert design, and end-to-end signal quality.
- Strong Python and/or Go scripting for production services and automation that safely touches real infrastructure.
- Executive communication skills, translating infrastructure health and operational risk into clear narratives for senior leadership, including non-technical stakeholders.
- Ability to operate in a high-ambiguity, low-process environment, building structure rather than inheriting it.
- Preferred Qualifications
- Experience operating customer-facing infrastructure or platform services, with 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 across AWS, Azure, and GCP alongside on-prem/colo, with unified observability and IaC.
- FinOps expertise: cloud spend attribution, TCO modeling across cloud vs. on-prem vs. colo, and translating cost data into workload placement recommendations.
- ITIL knowledge or an 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 al applicants. Thank you for your understanding and cooperation.
About D Matrix
Technology
d-Matrix develops digital in-memory computing chips designed to accelerate AI inference workloads, delivering high throughput and energy efficiency for data center deployments.
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