---
title: 'Director Site Reliability Engineer, AI Infrastructure at d-Matrix'
canonical: 'https://feeny.ai/job/director-site-reliability-engineer-ai-infrastructure-d-matrix-santa-clara-6vgcta048qbq'
type: 'job'
last_seen: '2026-10-16'
---

# Director Site Reliability Engineer, AI Infrastructure at d-Matrix

- **Company:** d-Matrix
- **Location:** Santa Clara, CA
- **Compensation:** $195k–$285k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-09-26
- **Last confirmed live:** 2026-10-16
- **Apply:** https://jobs.ashbyhq.com/d-matrix/505b7fa6-666a-44d5-9b23-88b7eec20502

## Job 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.

## Role Overview

d-Matrix designs and manufactures purpose-built AI inference silicon, and the infrastructure underpinning 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 function from the ground up, owning the infrastructure that development, validation, and customer-facing deployments run on — spanning colocation facilities, on-premises lab clusters, cloud environments (AWS, Azure, GCP), and customer-facing 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, all while remaining hands-on. You will partner closely with Software Tools, QA DevOps, and Engineering teams whose workflows run on this infrastructure, as well as Networking Operations and IT Operations, to drive reliability, cost efficiency, and the removal of technical debt.

## 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

## Company Overview
- **One-liner**: d-Matrix is building ultra-low latency, memory-centric AI inference hardware and software platforms for datacenter-scale generative AI workloads.
- **Entity Type**: Private (Series C, total raised ~$429M–$450M per conflicting reports)
- **Headquarters**: Santa Clara, California, USA
- **Founded**: 2019
- **Founders**: Sid Sheth (CEO) & Sudeep Bhoja (CTO / Founder)

## Core Business
- **Primary industries**: AI infrastructure, semiconductor / hardware acceleration, datacenter compute
- **Target customers**: Cloud providers, enterprises running large-scale generative AI inference (B2B)
- **Mission / purpose**: To transform AI from unsustainable to attainable by breaking through limits of latency, cost, and energy in inference.

## Products & Services
- **Corsair™** – AI inference accelerator platform (PCIe form factor, chiplet-based, 3D stacked DRAM) purpose-built for the decode phase of disaggregated inference. Works alongside GPUs for low-latency interactive AI.
- **JetStream™** – Purpose-built I/O accelerator for AI inference (networking fabric to scale accelerator-to-accelerator communication).
- **Aviator** – Software stack that orchestrates and optimizes inference workloads on d-Matrix hardware.
- **SquadRack™** – Industry’s first rack-scale, disaggregated standards-based solution for AI inference, built with infrastructure partners.

## Market Standing
- **Valuation**: Not publicly disclosed (private company)
- **Key metric**: Total funding – $429M (per CB Insights) or $450M (per company blog after $275M Series C). Series C announced in late 2025 / early 2026.
- **Notable investors**: Temasek, M12 (Microsoft’s venture arm), Playground Global, Nautilus Venture Partners, Industry Ventures, Mirae Asset Financial Group, Triatomic Capital, Bullhound Capital.
- **Growth signals**:
  - Corsair entered full production in June 2026.
  - Won “AI Processor Innovation Award” from AI Breakthrough in June 2026.
  - Filed 21+ patents in parallel computing, neural networks, NLP.
  - Opened engineering offices in Santa Clara, Toronto, Bengaluru, Sydney, and Belgrade – global expansion underway.

## Competitive Advantages
- **Memory-centric compute architecture (3DIMC™)** that eliminates latency bottlenecks caused by traditional memory-bound AI inference.
- Chiplet-based design enables scaling to 100B+ parameter models in a PCIe form factor.
- Disaggregated, standards-based rack-scale approach (SquadRack) that integrates seamlessly with existing datacenter infrastructure.
- Team of industry veterans who have shipped over 100 million chips and generated $5B+ in prior revenue.

## Strategic Focus
- Scaling production of Corsair to meet customer demand for agentic AI workloads (voice agents, coding tools, real-time inference).
- Building a heterogeneous compute ecosystem where d-Matrix accelerators complement GPUs rather than replace them.
- Expanding software stack (Aviator) and networking (JetStream) to deliver full-stack inference solutions.

## Why Work Here
- **Culture**: “Round pegs in square holes” – builders, innovators, dreamers. Emphasis on humility, direct communication, and collaboration.
- **Work model**: Remote & hybrid working model (global offices in Silicon Valley, Sydney, Bengaluru, Toronto, Belgrade).
- **Benefits**: Competitive pay and equity, health care, flexible time-off, paid paternity leave, 401k, on-site fitness centers, free food/snacks, peer coaching & development, team-building activities.
- **Engineering environment**: Work with world-leading engineers and researchers on cutting-edge AI hardware/software. Opportunity to shape the future of AI inference infrastructure.

## Sources
1. [d-matrix.ai – Homepage](https://www.d-matrix.ai/)
2. [d-matrix.ai – About / Leadership](https://www.d-matrix.ai/about/)
3. [d-matrix.ai – Careers](https://www.d-matrix.ai/careers/)
4. [d-matrix.ai – Corsair Production & AI Breakthrough Award](https://www.d-matrix.ai/announcements/d-matrix-corsair-ai-inference-platform-enters-full-production-to-meet-customer-demand/)
5. [CB Insights – d-Matrix Company Profile](https://www.cbinsights.com/company/d-matrix)
6. [Ashby – d-Matrix Jobs](https://jobs.ashbyhq.com/d-matrix)

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