Alibaba Cloud Intelligence-AI Infrastructure and its derivative fields-Hong Kong

岗位描述
1. Develop global GPUaaS integrators, inference platforms, model companies, and AI-native customers. Identify compute requirements across training, fine-tuning, and inference workloads, and build and convert a qualified AI infrastructure and MaaS pipeline.
2. Own the full lifecycle of GPUaaS, inference infrastructure, and MaaS opportunities, from requirement qualification, compute and product matching, POC validation, and commercial negotiation through production launch, compute and token growth, renewal, and expansion.
3. Assess GPU type, cluster scale, networking and storage, resource scheduling, and deployment approach for customer workloads. Understand inference throughput, latency, concurrency, and unit economics, and work with solution architects to develop executable AI infrastructure solutions.
4. Design integrated solutions covering GPUaaS access, dedicated or elastic GPU clusters, inference platform integration, model APIs, and MaaS. Move customers from technical validation to stable production while improving performance, cost, and resource utilization.
5. Articulate the capabilities and differentiated value of Alibaba Cloud GPU compute, MaaS, Qwen models, and related AI products. Lead business and technical discussions on model selection, fine-tuning, inference deployment, API consumption, and token-based pricing.
6. Develop GPUaaS integrators, inference platforms, and model companies as ecosystem partners. Drive joint solutions, technical integration, and go-to-market execution to reach more developers and end customers and scale adoption of AI compute and MaaS.
7. Independently drive customer decisions, commercial proposals, negotiation, contracting, and delivery coordination. Track GPU supply and demand, inference technologies, foundation models, and competitors, and translate market intelligence into product, pricing, and go-to-market recommendations.

岗位要求
1. Bachelor's degree or above, with 5+ years of experience in B2B sales, technical business development, pre-sales solutions, or product commercialization in cloud computing, AI infrastructure, or GenAI. Experience serving GPUaaS, inference platform, or model-company customers is preferred.
2. Understanding of AI infrastructure and GPUaaS business models, with working knowledge of GPU clusters, networking, storage, resource scheduling, and capacity planning; able to discuss resource specifications, performance, cost, and deployment options for training and inference workloads.
3. Understanding of foundation models, MaaS, model APIs, agents, multimodal AI, and inference services, including token-based pricing, throughput, latency, concurrency, and unit inference cost, with the ability to map products to customer use cases.
4. Proven ability to develop customers and partnerships from zero to one and independently manage discovery or archtect consultant/design, solution fit, POC execution, pricing, contract negotiation, and closing, moving projects from validation to production-scale usage.
5. Able to engage customer CTOs, infrastructure leaders, product owners, and engineering teams in substantive business and technical discussions, identify decision paths, and coordinate product, architecture, and delivery resources.
6. Business-negotiation-level English is required, including independent customer engagement, solution presentation, commercial-term discussion, contract negotiation, and effective cross-time-zone collaboration.
7. Strong commercial judgment, results orientation, and learning agility, with the ability to track developments in GPUs, inference infrastructure, model services, and the GenAI market and drive execution in a fast-paced environment.
8. Preferred: familiarity with AI compute ecosystems in the American continent and Singapore, or a technical advantage in Cloud, inference platforms, inference engines, model deployment, or inference performance optimization.