Solutions Architect

Job Type: Full-time |

Location:

San Francisco | Department:
Commercial | Reporting to:
Commercial Director, AI&HPC | Work Location Type: #On-site

IREN is a leading AI Cloud Service Provider, delivering large-scale GPU clusters for AI training and inference. IREN’s vertically integrated platform is underpinned by its expansive portfolio of grid‑connected land and data centers in renewable‑rich regions across the U.S. and Canada.

As we continue to expand our AI and high‑performance compute platform, IREN is hiring a Solutions Architect to partner with customers and support the design, deployment, and optimization of their workloads.

With 100% renewable energy, we build, own and operate our data centers and take pride in being at the forefront of sustainable solutions for the ever‑evolving applications of high‑performance compute. We believe that human progress is invaluable, but it should be done in the right way – responsibly, sustainably and having a positive impact on the communities we operate in.

• Post‑secondary education in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience
• 6+ years of experience in solutions architecture, systems engineering, infrastructure engineering, or customer‑facing technical roles supporting production workloads
• Strong understanding of AI infrastructure fundamentals, including GPU‑based compute systems, high‑performance networking, and storage architectures
• Demonstrated experience supporting distributed workloads for AI, machine learning, or high‑performance computing in production environments
• Hands‑on familiarity with GPU platforms commonly used for AI workloads and the surrounding software and networking ecosystem
• Experience working with workload orchestration or scheduling systems used in AI or HPC environments (e.g., Kubernetes and/or batch schedulers)
• Ability to design, document, and communicate scalable infrastructure architectures that align technical requirements with business objectives
• Proven ability to build trusted relationships with customers and clearly communicate complex technical concepts to both technical and non‑technical audiences
• Strong troubleshooting and analytical skills, with experience diagnosing performance, configuration, or infrastructure‑level issues
• Comfortable working cross‑functionally with commercial, engineering, and operations teams in fast‑moving environments

• Pre‑employment screening, including background checks will be required according to company policies.

• Serving as the primary technical authority for customers deploying AI, machine learning, and high‑performance compute workloads on IREN’s infrastructure
• Leading end‑to‑end technical engagement across the customer lifecycle, from initial discovery and architecture design through onboarding, validation, and steady‑state production
• Translating customer workload requirements into clear, executable infrastructure designs spanning GPU compute, networking, storage, security, and performance considerations
• Designing, documenting, and validating reference architectures for distributed training and inference workloads running at scale
• Leading proof‑of‑concept and pilot deployments, including environment setup, performance benchmarking, and readiness assessment against customer success criteria
• Diagnosing and resolving technical issues related to workload performance, system configuration, and infrastructure dependencies, in close partnership with internal engineering and operations teams
• Providing technical leadership during customer meetings, architecture reviews, and deployment planning sessions, clearly articulating trade‑offs and recommendations
• Partnering with Commercial to support technical aspects of customer evaluations, proposals, and deployment planning without acting as a pure sales role
• Acting as a conduit between customers and internal teams by synthesizing field learnings into structured feedback to improve platform reliability, tooling, and operational processes
• Contributing to the development of internal best practices, documentation, and repeatable deployment patterns to…