Solutions Architect, AI Infrastructure in Canada Creek, Nova Scotia at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Solutions Architect, AI Infrastructure in Canada.

This role sits at the intersection of advanced AI computing, large-scale infrastructure design, and customer-facing technical leadership. You will help design and deploy next-generation GPU-based data center environments that power AI, HPC, and accelerated computing workloads. Acting as a trusted technical advisor, you will work closely with enterprise customers and cloud partners to translate complex requirements into scalable, high-performance infrastructure solutions. The position involves deep collaboration with engineering, product, and field teams to ensure successful deployment and optimization of AI clusters. You will influence architecture decisions, troubleshoot performance challenges, and guide customers through the full lifecycle of AI infrastructure adoption. This is a highly technical, hands-on role with strong exposure to cutting-edge AI systems and real-world large-scale deployments.

In this role, you will lead the technical design, deployment, and optimization of large-scale AI and GPU infrastructure solutions, acting as the primary technical partner for customers and internal stakeholders. You will ensure systems are architected for performance, scalability, and reliability while supporting the full lifecycle from design to production.

• Lead end-to-end design and deployment of large-scale GPU-based AI and HPC infrastructure.
• Serve as the primary technical advisor for customers across architecture, deployment, and optimization phases.
• Collaborate with cloud partners to design and support data center deployments, including compute, storage, and networking systems.
• Guide customers through server, cluster, and network bring-up processes, including on-site support when required.
• Troubleshoot and optimize compute and networking performance across GPU clusters.
• Partner with engineering, product, and account teams to align on technical strategy and customer needs.
• Deliver technical presentations, workshops, and reference architectures to customers and stakeholders.
• Support evaluation and adoption of new technologies and contribute feedback to product roadmap discussions.
• Ensure infrastructure designs meet performance, scalability, and reliability requirements in production environments.

This role requires deep technical expertise in systems architecture, AI infrastructure, and data center technologies, combined with strong customer-facing and consulting capabilities. You should be comfortable working across hardware, software, networking, and AI workloads in complex enterprise environments.

• Bachelor’s, Master’s, or PhD in Engineering, Computer Science, Mathematics, or related field (or equivalent experience).
• 5+ years of experience in solution architecture, systems engineering, cloud engineering, or technical pre-sales roles.
• Strong understanding of GPU/CPU server architecture and system-level computing environments.
• Experience with data center networking (Ethernet, InfiniBand), storage, and infrastructure design.
• Knowledge of Linux systems, kernel-level concepts, and system software.
• Familiarity with DevOps/MLOps tools such as Docker, Kubernetes, and containerized environments.
• Experience troubleshooting distributed systems and performance optimization in compute clusters.
• Strong communication, presentation, and stakeholder management skills.
• Ability to manage multiple priorities in fast-paced, customer-driven environments.
• Hands-on experience with AI/HPC infrastructure deployment is highly valued.
• Familiarity with GPU ecosystems, networking technologies, and cluster management tools is a strong asset.

• Competitive base salary range aligned with experience and location.
• Equity opportunities as part of total compensation.
• Comprehensive health, dental, and vision coverage.
• Strong focus on professional growth, learning, and continuous development.
• Exposure to cutting-edge AI infrastructure and large-scale global deployments.
• Collaborative, innovation-driven engineering culture.
• Flexible work environment with occasional travel for customer engagements.
• Additional employee benefits supporting financial, physical, and personal wellbeing.