Highrise AI is a GPU-native infrastructure platform built for modern AI workloads. Designed for developers and enterprises operating in performance-critical and security-sensitive environments, Highrise delivers scalable GPU compute across dedicated clusters, managed cloud, and confidential environments.
🏢 About Highrise AI
Highrise combines bare-metal performance with full-stack orchestration, API-driven access, and hardware-enforced isolation to support training, fine-tuning, and production-scale deployment of AI models. From reserved GPU capacity to enterprise-grade confidential compute, Highrise provides flexible infrastructure models tailored to the needs of builders operating at scale. Highrise is a subsidiary of Hut 8 Corp., an energy infrastructure platform.
🎯 The Role
We are seeking a mid-level AI Infrastructure Operations Engineer to provide Tier 2 operational support for large-scale GPU compute and storage platforms. This hands-on role focuses on owning technical tickets, restoring service, investigating recurring issues, and maintaining reliable day-to-day operation of production AI clusters.
✅ Key Responsibilities
Own and manage escalated incidents, service requests, and problem tickets from initial technical triage through resolution, escalation, or documented handoff.
Diagnose compute and storage faults using system logs, monitoring dashboards, management interfaces, and approved diagnostic tools.
Assess severity and customer impact; coordinate with the NOC and site teams to restore service within operational and SLA targets.
Produce clear troubleshooting records, timely ticket updates, shift handovers, and actionable Tier 3 or OEM escalations.
Troubleshoot Linux servers, GPU health alerts, boot failures, firmware/driver issues, hardware faults, and resource availability problems.
Support node provisioning, reimaging, configuration changes, routine maintenance, and return-to-service validation using established automation and runbooks.
Investigate Kubernetes and Slurm node or workload failures, working with platform engineers when application or scheduler-level escalation is required.
Perform first-level analysis of connectivity or GPU communication symptoms and engage network or Tier 3 engineers for deeper fabric and performance investigation.
Monitor and troubleshoot distributed and high-performance storage systems, including capacity, throughput, availability, and client connectivity.
Investigate filesystem mount failures, storage-node or disk alerts, degraded services, and access or performance complaints.
Execute approved recovery, maintenance, and component replacement workflows with storage vendors and data hall technicians.
Assist with upgrades, planned maintenance, cluster expansions, and validation activities following established change controls.
Maintain accurate asset, configuration, and ticket records; improve runbooks, troubleshooting checklists, and knowledge articles.
Identify recurring incidents and automate repeatable operational work with scripts and existing infrastructure management tools.
Collaborate with remote engineering teams, on-site technicians, OEMs, and vendors to resolve issues safely and efficiently.
📌 Required Qualifications
Bachelor's degree in computer science, engineering, or related discipline, or equivalent hands-on experience.
3–6 years of experience supporting Linux servers, HPC, cloud, or data center infrastructure in a production environment.
Practical troubleshooting experience with enterprise compute hardware, BMC interfaces (iDRAC/iLO or equivalent), operating systems, and monitoring tools.
Working familiarity with storage technologies such as NFS, distributed filesystems, object storage, and storage performance fundamentals.
Experience using ticketing systems, change management procedures, and Bash or Python scripting for routine diagnostics and automation.
⭐ Desirable Experience
Exposure to NVIDIA GPU systems, InfiniBand/RDMA, Kubernetes, Slurm, or AI/HPC storage platforms is a strong advantage.
🎁 Benefits
At Highrise, you will directly influence the performance, reliability, and production readiness of large-scale AI clusters, work alongside experienced infrastructure engineers, and help define the technical standards for a growing global AI infrastructure platform.
🛂 Visa & Eligibility
This is a full-time, engineering role supporting large-scale AI compute infrastructure across multiple sites. Travel to data centers for cluster commissioning, acceptance, and complex troubleshooting will be required. Flexibility to assist with critical incidents or maintenance activities outside regular business hours is expected. This role is hybrid or remote depending on location. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
