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.  

• 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 support consistent customer outcomes
• Maintaining a working understanding of evolving AI infrastructure, distributed systems, and high-performance compute trends relevant to customer workloads

• 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