{
    "schema_version": "via_ai_product_manager_jobs_v1",
    "data_type": "ai_product_manager_jobs",
    "job": {
        "job_title": "AI Engineer",
        "job_level": "中级",AI生成
        "work_category": "全职",AI生成
        "department": "",
        "location": "香港",
        "work_mode": "现场办公",AI生成
        "job_category": "AI应用软件工程师"AI生成
    },
    "company": {
        "company_name": "某大型金融集团公司",
        "company_industry": "咨询",
        "company_size": "10000人以上",
        "company_website": "",
        "company_description": ""
    },
    "compensation": {
        "salary_range": {
            "min": 50000,
            "max": 80000,
            "currency": "CNY",
            "cycle": "month"
        },
        "benefits": ""
    },
    "requirements": {
        "working_years": 5,
        "degree": "本科",
        "language": "英文",AI生成
        "visa_support": "",
        "responsibilities": "",
        "requirements_text": "金融\n量化\n股票\nAI\nLLM\nRAG\nAgent\nResponsibilities\n• Design and develop AI-powered applications based on LLMs and Agent\nframeworks.\n• Build enterprise-grade RAG and knowledge management systems for\ninvestment research.\n• Develop AI workflows for financial document understanding, earnings call\nanalysis, news summarization and investment research automation.\n• Collaborate closely with Portfolio Managers and Equity Research teams to\nidentify opportunities where AI can improve research productivity.\n• Design scalable AI infrastructure and engineering platforms.\n• Evaluate and integrate state-of-the-art open-source and commercial\nfoundation models.\n• Continuously optimize AI system performance, latency, reliability and user\nexperience.\n• (Lead only) Drive technical architecture, mentor engineers and lead AI\nengineering best practices.\nRequirements\nTechnical\n• Strong software engineering experience with Python.\n• Hands-on experience building applications using LLMs.\n• Experience with:\no RAG\no AI Agents\no MCP\no Vector Databases\no LangGraph / LangChain / LlamaIndex (or similar frameworks)\n• Familiar with modern AI application architecture and cloud-native engineering.\n• Experience deploying production AI systems.\nPreferred\nExperience in one or more of the following:\n• Financial AI\n• NLP\n• Search & Recommendation\n• Knowledge Graph\n• Enterprise AI Platform\n• AI Copilot\n• Productivity Tools\nExposure to investment research, financial data or capital markets is a plus, but not\nmandatory.\nCandidate Profile\nWe are looking for engineers who are:\n• AI-native with strong curiosity and fast learning ability.\n• Passionate about applying emerging AI technologies to real business problems.\n• Comfortable working in a fast-paced, highly iterative environment.\n• Open-minded, collaborative and product-oriented.\n• Strong engineering mindset with the ability to turn research into production\nsystems.\nCandidates may come from:\n• Leading Internet companies\n• AI-native startups\n• Foundation model companies\n• AI platform teams\n• Financial AI companies\n• Applied AI teams within technology organizations\n认证资质\n人力资源服务许可证",
        "skills": [AI生成
            "Prompt工程",
            "RAG与检索增强",
            "工具调用/MCP",
            "数据库/缓存/向量库",
            "编程与代码实现"
        ],
        "preferred_qualifications": "",
        "job_highlights": ""
    },
    "contact": {
        "recruiter_name": "",
        "contact_methods": [
            {
                "type": "apply_link",
                "value": "https://www.zhipin.com/job_detail/36390896a860bf380nF82Nq5EFFQ.html"
            }
        ]
    },
    "posting": {
        "posting_id": "36390896a860bf380nF82Nq5EFFQ",
        "post_date": "",
        "hire_time": "",
        "update_date": "",
        "job_url": "https://www.zhipin.com/job_detail/36390896a860bf380nF82Nq5EFFQ.html"
    },
    "fulltext": "金融\n量化\n股票\nAI\nLLM\nRAG\nAgent\nResponsibilities\n• Design and develop AI-powered applications based on LLMs and Agent\nframeworks.\n• Build enterprise-grade RAG and knowledge management systems for\ninvestment research.\n• Develop AI workflows for financial document understanding, earnings call\nanalysis, news summarization and investment research automation.\n• Collaborate closely with Portfolio Managers and Equity Research teams to\nidentify opportunities where AI can improve research productivity.\n• Design scalable AI infrastructure and engineering platforms.\n• Evaluate and integrate state-of-the-art open-source and commercial\nfoundation models.\n• Continuously optimize AI system performance, latency, reliability and user\nexperience.\n• (Lead only) Drive technical architecture, mentor engineers and lead AI\nengineering best practices.\nRequirements\nTechnical\n• Strong software engineering experience with Python.\n• Hands-on experience building applications using LLMs.\n• Experience with:\no RAG\no AI Agents\no MCP\no Vector Databases\no LangGraph / LangChain / LlamaIndex (or similar frameworks)\n• Familiar with modern AI application architecture and cloud-native engineering.\n• Experience deploying production AI systems.\nPreferred\nExperience in one or more of the following:\n• Financial AI\n• NLP\n• Search & Recommendation\n• Knowledge Graph\n• Enterprise AI Platform\n• AI Copilot\n• Productivity Tools\nExposure to investment research, financial data or capital markets is a plus, but not\nmandatory.\nCandidate Profile\nWe are looking for engineers who are:\n• AI-native with strong curiosity and fast learning ability.\n• Passionate about applying emerging AI technologies to real business problems.\n• Comfortable working in a fast-paced, highly iterative environment.\n• Open-minded, collaborative and product-oriented.\n• Strong engineering mindset with the ability to turn research into production\nsystems.\nCandidates may come from:\n• Leading Internet companies\n• AI-native startups\n• Foundation model companies\n• AI platform teams\n• Financial AI companies\n• Applied AI teams within technology organizations\n认证资质\n人力资源服务许可证"
}