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.
Role Overviewd-Matrix designs and manufactures purpose-built AI inference silicon, and the infrastructure behind our engineering organization must be as reliable and scalable as the chips we build. This role builds and leads d-Matrix’s Site Reliability Engineering (SRE) function from the ground up. You will own the infrastructure that development, validation, and customer-facing deployments run on, spanning colocation facilities, on-premises lab clusters, cloud environments (AWS, Azure, GCP), and platform services. You will hire and grow the team, set technical direction, own SLOs for critical systems, and serve as the senior escalation point for incidents, while staying hands-on. You will partner closely with Software Tools, QA DevOps, Engineering, Networking Operations, and IT Operations to improve reliability, cost efficiency, and technical debt.
What You Will DoBuild 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.
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 SRE processes: 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 root cause analysis (RCA) framework.
Own the 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, 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, TCO modeling, and workload placement decisions.
Lead the migration from ad-hoc JBOD storage to an enterprise-grade shared storage platform across on-prem, colocation, and cloud, including architecture, vendor selection, and disaster recovery design.
Bachelor’s or Master’s degree 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 rather than managing a steady-state team.
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 from a reactive ops background.
Deep Linux systems expertise, including bare-metal operations and enterprise shared storage (NAS/SAN, NFS/SMB at scale, 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 (Terraform, 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 (Prometheus, Grafana, Datadog, Splunk, or equivalent) for SLO 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, building structure rather than inheriting it.
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 HPC job schedulers (Slurm, LSF, or equivalent), including setup, tuning, and integration with infrastructure automation.
Multi-cloud hybrid operations across AWS, Azure, and GCP alongside on-prem and colo, with unified observability and IaC.
FinOps expertise, including cloud spend attribution, TCO modeling across cloud, on-prem, and colo, 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 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.
Skills Required
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field
- 15+ years of experience in SRE, infrastructure engineering, or production engineering
- 5+ years leading SRE or infrastructure engineering teams
- Experience building or significantly rebuilding an SRE or infrastructure function
- Track record establishing SRE practices, including SLOs, on-call frameworks, observability, and operational culture
- Deep Linux systems expertise, including bare-metal operations and enterprise shared storage
- Experience with NAS/SAN, NFS/SMB at scale, snapshots, replication, and hybrid-cloud storage integration
- Experience operating colocation and on-premises hardware at scale
- Experience with server lifecycle management, power and cooling, and rack-level networking
- Production-scale Terraform and Ansible expertise
- Kubernetes cluster operations, including lifecycle management, workload reliability, storage, and RBAC
- Ownership of observability platforms such as Prometheus, Grafana, Datadog, or Splunk
- Strong Python and/or Go scripting skills for infrastructure automation and production services
- Executive communication skills for explaining infrastructure health and operational risk
- Ability to operate in a high-ambiguity, low-process environment
- Experience operating customer-facing infrastructure or platform services
- Experience with InfiniBand, RoCE, or NVLink
- HPC job scheduler experience with Slurm, LSF, or equivalent
- Multi-cloud hybrid operations across AWS, Azure, GCP, on-premises, and colocation environments
- FinOps expertise, including cloud spend attribution and TCO modeling
- ITIL or equivalent incident, problem, and change management knowledge
- Published technical writing, conference talks, or open-source contributions
What We Do
d-Matrix is building a new way of doing datacenter AI inferencing using in-memory computing (IMC) techniques with chiplet level scale-out interconnects. Founded in 2019, d-Matrix has attacked the physics of memory-compute integration using innovative circuit techniques, ML tools, software and algorithms; solving the memory-compute integration problem, which is the final frontier in AI compute efficiency.








