Overview

We are seeking a highly skilled Solution Architect with strong expertise in GPU-based cloud infrastructure, capable of bridging technical architecture and business strategy. This role will design scalable GPU cloud solutions, work closely with customers and partners, and translate complex requirements into actionable architectures and business value.

Key Responsibilities

1. Technical Architecture

• Design and architect GPU cloud platforms (including H100/H200/B200/L40S, GB200/GB300 clusters, multi-rack setup).

• Plan and optimize infrastructure topology, including network, storage, security, GPU scheduling, and virtualization/containerization (Kubernetes, Slurm, etc.).

• Evaluate hardware options and set clear performance benchmarks/TCO/performance per watt.

• Define best practices for MLOps / LLM training / inference stacks.

• Provide reference architectures and solution playbooks for different customer use cases.

2. Pre-Sales & Business Enablement

-Work with customers to understand business needs and translate them into technical solutions.

• Prepare solution proposals, cost estimates, TCO analysis, and ROI models.

• Present technical solutions to executives, VPs, CTOs, or procurement teams.

• Support proof-of-concepts (POC), demo environments, and customer onboarding.

• Communicate competitive advantages and differentiate services against AWS / Azure / other GPU providers.

3. Cross-Team Collaboration

• Work with product, engineering, and operations teams to ensure solution feasibility.

• Provide feedback for roadmap planning and service offerings.

• Collaborate with data center teams on capacity planning, expansion strategy, and reliability.

• Document solution standards, guidelines, and operational run-books.

4. Customer Success & Long-Term Strategy

• Act as a trusted technical advisor for key enterprise customers.

• Propose scaling strategies, cost optimization, and continuous performance improvements.

• Gather customer requirements to influence product direction & pricing strategy.

• Build long-term architecture visions and solution frameworks for AI workloads.

Qualifications Required

• Bachelor’s/Master’s in Computer Science, Engineering, or related field.

• 5+ years experience in cloud architecture / infrastructure / solution engineering.

• Strong understanding of GPU workloads, parallel computing, AI/ML pipelines, and LLM training/inference.

• Hands-on knowledge of:

o Kubernetes / Docker / Slurm / Ray

o Linux, HPC, networking fundamentals

o GPU resource management & scheduling

• Experience in customer-facing technical roles (pre-sale, consulting, PoC, enterprise projects).

• Proven ability to explain complex ideas to business stakeholders and non-technical audiences.

Preferred

• Experience with data center operations or multi-rack GPU deployment.

• Familiar with cloud economics / TCO analysis / business modeling.

• Strong presentation skills & ability to write proposals.

• Understanding of security/compliance standards (ISO27001, SOC2, etc.).

• Multi-language ability (English / Chinese / Japanese) is a plus.

Soft Skills

• Solution-oriented and business-driven mindset.

• Strong communication and client engagement skills.

• Able to work independently under pressure.

• Strategic thinker with hands-on execution ability.

• Team player across departments (Product, Ops, Engineering, Sales).