{
    "schema_version": "via_ai_product_manager_jobs_v1",
    "data_type": "ai_product_manager_jobs",
    "job": {
        "job_title": "Sales Intern - Sunnyvale",
        "job_level": "实习",AI生成
        "work_category": "实习",AI生成
        "department": "阿里云",
        "location": "森尼韦尔",
        "work_mode": "未披露",AI生成
        "job_category": "销售类"AI生成
    },
    "company": {
        "company_name": "阿里云",
        "company_industry": "云计算 / 人工智能",
        "company_size": "10000人以上",
        "company_website": "alibaba.com",
        "company_description": "阿里云提供云基础设施、AI模型、智能体和计算服务。"
    },
    "compensation": {
        "salary_range": {
            "min": "",
            "max": "",
            "currency": "未披露",
            "cycle": "未披露"
        },
        "benefits": "Top CS students often choose between FAIR, Google Brain, or quant firms. We offer a third path: shaping how the next wave of companies adopts foundational AI and cloud infrastructure. Your work will directly influence which startups build on Alibaba Cloud—and how enterprises rethink their digital backbone."
    },
    "requirements": {
        "working_years": "",
        "degree": "未披露",
        "language": "未披露",AI生成
        "visa_support": "未披露",
        "responsibilities": "What You’ll Do\nThis isn’t a traditional sales internship. You’ll operate at the intersection of deep tech and go-to-market strategy, working alongside solutions architects and product leads to help technical buyers understand how Alibaba Cloud solves their hardest challenges. \nYou will: \n1. Analyze customer architectures and map pain points (e.g., high inference latency, vendor lock-in, data silos) to Alibaba Cloud capabilities like Elastic GPU Service, PAI (Model Studio), or AnalyticDB \n2. Research competitive landscapes across AWS/Azure/GCP—and articulate differentiated technical value (e.g., cost-performance ratio for LLM fine-tuning, multi-region disaster recovery SLAs) \n3. Co-develop technical outreach content: from concise LinkedIn threads on cloud cost optimization to demo scripts for GenAI use cases \n4. Participate in technical discovery calls with engineering teams—listening, synthesizing, and translating requirements into solution narratives \n5. Contribute to internal knowledge bases used by global sales engineers (think: “How would you position ApsaraDB vs. Amazon Aurora for a fintech startup?”)\nYou’ll be measured not by dials made, but by insights generated.",
        "requirements_text": "Who You Are\n1. Pursuing a BS/MS in Computer Science, Computer Engineering, or a closely related field at a technical university.\n2. You’ve built something—whether it’s a distributed system project, an LLM-powered app, or a Kubernetes cluster—and you understand trade-offs in real systems.\n3. You can read an architecture diagram as fluently as code, and you care about why a solution works—not just that it does.\n4. You enjoy explaining technical concepts—but only when they solve a real problem.\n5. You’re intellectually curious about how technology creates economic value at scale. \n6. Authorized to work in the U.S. (CPT/OPT eligible students are encouraged to apply).\nNote: You don’t need sales experience. But if you’ve ever convinced a teammate to adopt your design—or written documentation so clear others called it “magical”—you already have the core skill.\nWhy This Matters\nTop CS students often choose between FAIR, Google Brain, or quant firms. We offer a third path: shaping how the next wave of companies adopts foundational AI and cloud infrastructure. Your work will directly influence which startups build on Alibaba Cloud—and how enterprises rethink their digital backbone.\nThis internship is designed for those who want to stay close to the metal while driving commercial impact.",
        "skills": [AI生成
            "Kubernetes",
            "大语言模型"
        ],
        "preferred_qualifications": "未披露",
        "job_highlights": "Top CS students often choose between FAIR, Google Brain, or quant firms. We offer a third path: shaping how the next wave of companies adopts foundational AI and cloud infrastructure. Your work will directly influence which startups build on Alibaba Cloud"
    },
    "contact": {
        "recruiter_name": "未披露",
        "contact_methods": [
            {
                "type": "apply_link",
                "value": "https://campus-talent.alibaba.com/campus/position/199904280012?deptCodes="
            }
        ]
    },
    "posting": {
        "posting_id": "199904280012",
        "post_date": "2026-04-17",
        "hire_time": "未披露",
        "update_date": "20260917",
        "job_url": "https://campus-talent.alibaba.com/campus/position/199904280012?deptCodes="
    },
    "fulltext": "Sales Intern - Sunnyvale\nSales Intern - Sunnyvale\n\n基础信息\n毕业起止时间要求：2027-11-01 - 2030-01-01\n职位类别：销售类\n招聘项目：阿里巴巴日常实习生\n工作地点：森尼韦尔\n\n职位描述\nWhat You’ll Do\nThis isn’t a traditional sales internship. You’ll operate at the intersection of deep tech and go-to-market strategy, working alongside solutions architects and product leads to help technical buyers understand how Alibaba Cloud solves their hardest challenges. \nYou will: \n1. Analyze customer architectures and map pain points (e.g., high inference latency, vendor lock-in, data silos) to Alibaba Cloud capabilities like Elastic GPU Service, PAI (Model Studio), or AnalyticDB \n2. Research competitive landscapes across AWS/Azure/GCP—and articulate differentiated technical value (e.g., cost-performance ratio for LLM fine-tuning, multi-region disaster recovery SLAs) \n3. Co-develop technical outreach content: from concise LinkedIn threads on cloud cost optimization to demo scripts for GenAI use cases \n4. Participate in technical discovery calls with engineering teams—listening, synthesizing, and translating requirements into solution narratives \n5. Contribute to internal knowledge bases used by global sales engineers (think: “How would you position ApsaraDB vs. Amazon Aurora for a fintech startup?”)\nYou’ll be measured not by dials made, but by insights generated.\n\n职位要求\nWho You Are\n1. Pursuing a BS/MS in Computer Science, Computer Engineering, or a closely related field at a technical university.\n2. You’ve built something—whether it’s a distributed system project, an LLM-powered app, or a Kubernetes cluster—and you understand trade-offs in real systems.\n3. You can read an architecture diagram as fluently as code, and you care about why a solution works—not just that it does.\n4. You enjoy explaining technical concepts—but only when they solve a real problem.\n5. You’re intellectually curious about how technology creates economic value at scale. \n6. Authorized to work in the U.S. (CPT/OPT eligible students are encouraged to apply).\nNote: You don’t need sales experience. But if you’ve ever convinced a teammate to adopt your design—or written documentation so clear others called it “magical”—you already have the core skill.\nWhy This Matters\nTop CS students often choose between FAIR, Google Brain, or quant firms. We offer a third path: shaping how the next wave of companies adopts foundational AI and cloud infrastructure. Your work will directly influence which startups build on Alibaba Cloud—and how enterprises rethink their digital backbone.\nThis internship is designed for those who want to stay close to the metal while driving commercial impact.\n\n在招业务\n阿里云\nWhat You’ll Do\nThis isn’t a traditional sales internship. You’ll operate at the intersection of deep tech and go-to-market strategy, working alongside solutions architects and product leads to help technical buyers understand how Alibaba Cloud solves their hardest challenges. \nYou will: \n1. Analyze customer architectures and map pain points (e.g., high inference latency, vendor lock-in, data silos) to Alibaba Cloud capabilities like Elastic GPU Service, PAI (Model Studio), or AnalyticDB \n2. Research competitive landscapes across AWS/Azure/GCP—and articulate differentiated technical value (e.g., cost-performance ratio for LLM fine-tuning, multi-region disaster recovery SLAs) \n3. Co-develop technical outreach content: from concise LinkedIn threads on cloud cost optimization to demo scripts for GenAI use cases \n4. Participate in technical discovery calls with engineering teams—listening, synthesizing, and translating requirements into solution narratives \n5. Contribute to internal knowledge bases used by global sales engineers (think: “How would you position ApsaraDB vs. Amazon Aurora for a fintech startup?”)\nYou’ll be measured not by dials made, but by insights generated.\nWho You Are\n1. Pursuing a BS/MS in Computer Science, Computer Engineering, or a closely related field at a technical university.\n2. You’ve built something—whether it’s a distributed system project, an LLM-powered app, or a Kubernetes cluster—and you understand trade-offs in real systems.\n3. You can read an architecture diagram as fluently as code, and you care about why a solution works—not just that it does.\n4. You enjoy explaining technical concepts—but only when they solve a real problem.\n5. You’re intellectually curious about how technology creates economic value at scale. \n6. Authorized to work in the U.S. (CPT/OPT eligible students are encouraged to apply).\nNote: You don’t need sales experience. But if you’ve ever convinced a teammate to adopt your design—or written documentation so clear others called it “magical”—you already have the core skill.\nWhy This Matters\nTop CS students often choose between FAIR, Google Brain, or quant firms. We offer a third path: shaping how the next wave of companies adopts foundational AI and cloud infrastructure. Your work will directly influence which startups build on Alibaba Cloud—and how enterprises rethink their digital backbone.\nThis internship is designed for those who want to stay close to the metal while driving commercial impact.",
    "standard_classification": {
        "std_category_code": "B020",
        "std_aux_codes": [],
        "std_category_status": null,
        "std_taxonomy_version": "20261104"
    }
}