Alibaba Cloud
Business Development Director, AI-native Business-Global Strategic Account
Alibaba Cloud, Sunnyvale, California, United States, 94087
Responsibilities
Build and own relationships with AI-native companies founders, CTOs, engineers, and product leaders across the U.S.
Understand technical architectures and business models of AI-native companies—including LLM fine-tuning, RAG pipelines, AI agent orchestration, computer vision, and generative applications.
Position Alibaba Cloud’s AI stack—including Tongyi Qianwen (Qwen) models, PAI (Platform for AI), GPU/ML-optimized instances, OSS for vector storage, and serverless inference—as the optimal infrastructure for cost, performance, and innovation.
Drive adoption and expansion from initial proof-of-concept through scaled production usage, with a focus on AI-specific consumption (e.g., GPU hours, model hosting, API calls).
Collaborate with Solutions Architects and AI specialists to design tailored, competitive solutions that solve real startup pain points: cost-efficient training, low-latency inference, global deployment, etc.
Navigate complex technical evaluations and help startups compare Alibaba Cloud vs. competitors (AWS Bedrock, Azure OpenAI, GCP Vertex AI) based on openness, pricing, and flexibility.
Represent Alibaba Cloud at AI conferences (e.g., NeurIPS, AWS re:Invent Startup events, TechCrunch Disrupt), incubators (Y Combinator, a16z events), and VC partner meetings.
Act as the voice of the customer—feeding insights back to product teams to improve developer experience, documentation, and AI tooling.
Job Requirements
Bachelor’s degree in Computer Science, Engineering, or related technical field (or equivalent practical experience).
3+ years in a customer-facing technical sales, solutions engineering, or developer relations role—preferably in cloud, AI/ML, or infrastructure.
Deep understanding of modern AI stacks: familiarity with transformers, fine-tuning, quantization, vector databases, LangChain/LlamaIndex, inference optimization, and MLOps tools.
Proven ability to explain complex technical concepts clearly to both engineers and non-technical business audiences.
Exceptional interpersonal and communication skills—you build trust quickly and thrive in ambiguous, founder-led environments.
Willingness to travel extensively (~50% of time) across the U.S. to meet customers in person.
Preferred
Experience working with or at an AI-native companies (as employee, advisor, or investor).
Hands-on experience deploying models on cloud platforms (Alibaba Cloud, AWS, GCP, Azure).
Familiarity with open-weight models, model serving frameworks (vLLM, TGI), and cost/performance tradeoffs in inference.
Genuine enthusiasm for AI innovation—you follow arXiv papers, experiment with open models (e.g., Llama, Mistral, Qwen), or build side projects with AI agents.
Existing network in the U.S. AI/VC/startup ecosystem.
#J-18808-Ljbffr
Build and own relationships with AI-native companies founders, CTOs, engineers, and product leaders across the U.S.
Understand technical architectures and business models of AI-native companies—including LLM fine-tuning, RAG pipelines, AI agent orchestration, computer vision, and generative applications.
Position Alibaba Cloud’s AI stack—including Tongyi Qianwen (Qwen) models, PAI (Platform for AI), GPU/ML-optimized instances, OSS for vector storage, and serverless inference—as the optimal infrastructure for cost, performance, and innovation.
Drive adoption and expansion from initial proof-of-concept through scaled production usage, with a focus on AI-specific consumption (e.g., GPU hours, model hosting, API calls).
Collaborate with Solutions Architects and AI specialists to design tailored, competitive solutions that solve real startup pain points: cost-efficient training, low-latency inference, global deployment, etc.
Navigate complex technical evaluations and help startups compare Alibaba Cloud vs. competitors (AWS Bedrock, Azure OpenAI, GCP Vertex AI) based on openness, pricing, and flexibility.
Represent Alibaba Cloud at AI conferences (e.g., NeurIPS, AWS re:Invent Startup events, TechCrunch Disrupt), incubators (Y Combinator, a16z events), and VC partner meetings.
Act as the voice of the customer—feeding insights back to product teams to improve developer experience, documentation, and AI tooling.
Job Requirements
Bachelor’s degree in Computer Science, Engineering, or related technical field (or equivalent practical experience).
3+ years in a customer-facing technical sales, solutions engineering, or developer relations role—preferably in cloud, AI/ML, or infrastructure.
Deep understanding of modern AI stacks: familiarity with transformers, fine-tuning, quantization, vector databases, LangChain/LlamaIndex, inference optimization, and MLOps tools.
Proven ability to explain complex technical concepts clearly to both engineers and non-technical business audiences.
Exceptional interpersonal and communication skills—you build trust quickly and thrive in ambiguous, founder-led environments.
Willingness to travel extensively (~50% of time) across the U.S. to meet customers in person.
Preferred
Experience working with or at an AI-native companies (as employee, advisor, or investor).
Hands-on experience deploying models on cloud platforms (Alibaba Cloud, AWS, GCP, Azure).
Familiarity with open-weight models, model serving frameworks (vLLM, TGI), and cost/performance tradeoffs in inference.
Genuine enthusiasm for AI innovation—you follow arXiv papers, experiment with open models (e.g., Llama, Mistral, Qwen), or build side projects with AI agents.
Existing network in the U.S. AI/VC/startup ecosystem.
#J-18808-Ljbffr