Business Development Director, AI-native Business-Global Strategic Account

Alibaba Cloud; Sunnyvale (CA); Sur place; USD 100 000 - 150 000; Plein temps

Résumé du poste

Alibaba Cloud is seeking a technically-savvy professional to strengthen relationships with AI-native companies in Sunnyvale, CA. The ideal candidate will possess a Bachelor’s degree in a relevant field and have over 3 years in customer-facing roles tied to AI or cloud technology. They will manage the adoption of Alibaba’s AI solutions, needing deep knowledge of modern AI stacks, exceptional communication skills, and a network in the U.S. startup ecosystem alongside willingness to travel frequently.

Qualifications

• 3+ years in a customer-facing technical sales or solutions engineering role, preferably in cloud or AI.
• Deep understanding of modern AI stacks and related technologies.
• Ability to explain complex concepts to technical and non-technical audiences.

Responsabilités

• Build and manage relationships with AI-native company leaders across the U.S.
• Position Alibaba Cloud’s AI stack as the optimal infrastructure.
• Drive adoption from proof-of-concept to scaled production.

Connaissances

Customer-facing technical sales

Solutions engineering

Developer relations

Interpersonal skills

Communication skills

Formation

Bachelor’s degree in Computer Science, Engineering, or related field

Outils

AI stack tools (like TensorFlow, PyTorch)

Cloud platforms (Alibaba Cloud, AWS, GCP, Azure)

MLOps tools

Description du poste

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.
• Navigated 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 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.