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Source: Hut 8 careers · View original posting
From Hut 8's posting. “We” and “our” refer to the employer.
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.
ROLE OVERVIEW
We are seeking a principal-level, hands-on AI Systems Engineer to design, deploy, integrate, and operate the supporting infrastructure required for large-scale AI compute clusters. Working alongside senior compute, networking, and infrastructure engineers, this person will lead the deployment and configuration of general-purpose compute, virtualization, high-performance storage, infrastructure services, identity management, and security platforms.
The engineer will be responsible for bringing these systems from initial installation through integration, validation, and production acceptance. Following deployment, this person will provide Tier 3 technical escalation, advanced troubleshooting, and ongoing optimization of production infrastructure.
Education and Experience
Bachelor's degree in computer science, engineering, information technology, or related discipline, or equivalent practical experience.
10+ years of hands-on experience engineering and operating enterprise, cloud, HPC, or large-scale data center infrastructure.
Expert-level Linux systems administration, troubleshooting, automation, and infrastructure integration experience.
Strong experience with enterprise x86 platforms, virtualization technologies, and automated provisioning solutions.
Hands-on experience deploying and supporting high-performance or distributed storage platforms, preferably WEKA or VAST Data.
Strong understanding of DNS, DHCP, IPAM, identity management, SSO, RBAC, and core infrastructure services.
Experience with infrastructure automation using Python, Bash, Ansible, Terraform, or equivalent technologies.
Familiarity with security infrastructure, compliance requirements, monitoring, and enterprise authentication systems.
Experience supporting AI/HPC clusters, GPU infrastructure, or large-scale distributed computing environments is highly desirable.
Core Competencies
Expert-level troubleshooting and problem-solving across hardware, operating systems, virtualization, storage, and infrastructure services.
Strong ownership of deployment outcomes, operational reliability, system performance, and technical documentation.
Ability to independently design and implement complex infrastructure solutions while collaborating with senior engineering peers.
Highly analytical, detail-oriented, and comfortable operating in fast-paced, mission-critical environments.
Excellent written and verbal communication skills with engineering leadership, vendors, and operational stakeholders.
Continuous improvement mindset with a strong emphasis on automation, standardization, and operational efficiency.
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.
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.
Work with bright, driven peers from a range of educational and professional backgrounds including software development, energy, engineering, entrepreneurship, investment banking, private equity, and management consulting
Design and pitch new products, services, and other initiatives to a leadership team consisting of serial entrepreneurs and seasoned executives and backed by a board of directors consisting of industry veterans of energy, finance, and government
Debate ideas and alternatives in a truly meritocratic setting where the learning curve is steep and the lessons come from both senior and junior members of the team
Build a lifelong network of friends and professional connections at the cutting-edge intersection of technology, energy, and infrastructure
LAYIQ is an independent job-discovery service. This listing does not imply a partnership with or endorsement by the employer. Review the original posting for current details and availability.
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