GPU Cloud Solution Architect for AI Inference

Starry Recruitment; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Starry Recruitment is seeking a Solution Architect to support enterprise customers using GPU cloud infrastructure for AI and inference workloads. You will be the primary technical contact for international, English-speaking clients, helping them design, deploy, and optimize workloads on GPU cloud platforms.

The role requires a strong background in cloud and GPU infrastructure, networking, Kubernetes, and AI infrastructure, with the ability to communicate clearly with both technical and business

Qualifications

• 5-10 years of experience in solution architecture, cloud infrastructure, AI infrastructure, GPU infrastructure, networking, DevOps / SRE, or related technical roles.

Responsibilities

• Act as the technical point of contact for enterprise customers using GPU cloud / AI infrastructure services.
• Understand customer requirements around AI inference workloads and translate them into practical technical solutions.
• Design GPU cloud solutions covering GPU compute, networking, storage, deployment architecture, monitoring, and reliability.
• Support technical discussions, solution presentations, PoCs, customer onboarding, and troubleshooting.
• Work closely with engineering, product, and business teams to ensure customer requirements are delivered effectively.
• Help customers optimize inference performance, GPU utilization, network performance, cost efficiency, and deployment reliability.
• Provide customer feedback to internal teams to improve platform capabilities and service quality.

Skills

Solution architecture

Cloud infrastructure

AI infrastructure

GPU infrastructure

Networking

DevOps / SRE

Job description

Starry Recruitment is seeking a Solution Architect to support enterprise customers using GPU cloud infrastructure for AI and inference workloads. You will be the primary technical contact for international, English-speaking clients, helping them design, deploy, and optimize workloads on GPU cloud platforms.

The role requires a strong background in cloud and GPU infrastructure, networking, Kubernetes, and AI infrastructure, with the ability to communicate clearly with both technical and business