AI Infrastructure Operations Engineer - Compute & Storage - Highrise AI

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.

Working closely with the NOC, on-site data hall technicians, SRE teams, and senior infrastructure engineers, the engineer will troubleshoot Linux-based compute nodes, GPU systems, storage services, and their supporting software. Complex or systemic issues will be escalated to Tier 3 engineering with clear diagnostics and supporting evidence., Tier 2 Incident and Ticket Management

• 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.

Compute and GPU Platform Operations

• 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.

Storage Operations and Troubleshooting

• 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.

• Support operational tasks across file, object, and block storage platforms as deployed at Highrise sites.

Operational Readiness and Continuous Improvement

• 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., 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.

• 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.

• Exposure to NVIDIA GPU systems, InfiniBand/RDMA, Kubernetes, Slurm, or AI/HPC storage platforms is a strong advantage.

Core Competencies

• Structured, evidence-driven troubleshooting with sound judgment on when to remediate, collaborate, or escalate.

• Strong ownership of tickets, attention to operational detail, and commitment to reliable customer service.

• Ability to work effectively across NOC, SRE, hardware, network, storage, and Tier 3 engineering teams.

• Clear written and verbal communication in English.

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.

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.

Beyond infrastructure, Highrise integrates disciplined operations, advanced automation, and on-site engineering expertise to sustain high uptime and predictable performance across deployments. These capabilities extend beyond Highrise-owned fleets: through managed services, Highrise also operates third-party GPU hardware on behalf of customers and partners, applying the same operational standards to infrastructure it does not own.

Highrise is a subsidiary of Hut 8 Corp., an energy infrastructure platform. Hut 8 integrates power, digital infrastructure, and compute at scale. Highrise serves as the compute and operations layer-designing, deploying, and operating next-generation GPU clusters from commissioning through production.