{
    "schema_version": "via_ai_product_manager_jobs_v1",
    "data_type": "ai_product_manager_jobs",
    "job": {
        "job_title": "Senior LLM Engineer",
        "job_level": "高级",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": "江苏优阳",
        "company_industry": "计算机服务",
        "company_size": "0-20人",
        "company_website": "",
        "company_description": ""
    },
    "compensation": {
        "salary_range": {
            "min": 35000,
            "max": 45000,
            "currency": "CNY",
            "cycle": "month"
        },
        "benefits": ""
    },
    "requirements": {
        "working_years": 10,
        "degree": "硕士",
        "language": "英文",AI生成
        "visa_support": "",
        "responsibilities": "",
        "requirements_text": "大模型算法\n自然语言处理算法\n算法工程化经验\nPython\n一、Role Objective\n1、The Senior LLM Engineer will help us accelerate the development of production-ready Agentic AI applications and prototypes that demonstrate tangible business value.\n2、The role will be hands-on and engineering-focused, covering the full lifecycle from solution design and prototyping through integration, evaluation, deployment, and continuous improvement.\n二、What We Are Looking For\nThe candidate should have strong hands-on experience in:\n1、Designing and building LLM-powered applications and agentic workflows\n2、Developing multi-step AI workflows involving planning, tool use, execution, retries, and structured outputs\n3、Integrating LLM solutions with APIs, enterprise systems, databases, and application front ends\n4、Working with UI integration for agentic applications, including connecting backend agent systems to frontend interfaces and supporting debugging or fixes in end-to-end flows\n5、Designing robust application architecture rather than only building prompt-based prototypes\n6、Python and modern software engineering practices\n7、LLM frameworks and orchestration approaches for agents, tools, retrieval, and workflow management, including tools such as LangGraph and similar agent orchestration frameworks\n8、RAG, embeddings, vector search, structured data retrieval, and context management\n9、LLM evaluation, testing, observability, prompt/version management, and production monitoring\n10、Managing reliability, latency, token usage, cost, security, and failure handling in production LLM applications\n三、Seniority Expectations\n1、We are specifically looking for someone at Senior Engineer level who can:\n2、Take ownership of a complex LLM use case with limited supervision\nTranslate a business problem into an appropriate technical design\n3、Make sound architectural decisions, including when to use agentic or multi-agent approaches versus simpler solutions\n4、Identify technical risks and trade-offs early\n5、Write maintainable, production-quality code\n6、Review and improve the work of other engineers where needed\n7、Collaborate effectively with Data Scientists, Engineers, Product/Business teams, and technical stakeholders\n8、Help raise the engineering quality of the team through good practices and technical judgement",
        "skills": [AI生成
            "Agent系统构建",
            "RAG与检索增强",
            "模型训练与算法优化",
            "编程与代码实现",
            "数据库/缓存/向量库",
            "上下文/知识工程"
        ],
        "preferred_qualifications": "",
        "job_highlights": ""
    },
    "contact": {
        "recruiter_name": "",
        "contact_methods": [
            {
                "type": "apply_link",
                "value": "https://www.zhipin.com/job_detail/7fac5d2a40f751d00nJz3dq-GFFQ.html"
            }
        ]
    },
    "posting": {
        "posting_id": "7fac5d2a40f751d00nJz3dq-GFFQ",
        "post_date": "",
        "hire_time": "",
        "update_date": "",
        "job_url": "https://www.zhipin.com/job_detail/7fac5d2a40f751d00nJz3dq-GFFQ.html"
    },
    "fulltext": "大模型算法\n自然语言处理算法\n算法工程化经验\nPython\n一、Role Objective\n1、The Senior LLM Engineer will help us accelerate the development of production-ready Agentic AI applications and prototypes that demonstrate tangible business value.\n2、The role will be hands-on and engineering-focused, covering the full lifecycle from solution design and prototyping through integration, evaluation, deployment, and continuous improvement.\n二、What We Are Looking For\nThe candidate should have strong hands-on experience in:\n1、Designing and building LLM-powered applications and agentic workflows\n2、Developing multi-step AI workflows involving planning, tool use, execution, retries, and structured outputs\n3、Integrating LLM solutions with APIs, enterprise systems, databases, and application front ends\n4、Working with UI integration for agentic applications, including connecting backend agent systems to frontend interfaces and supporting debugging or fixes in end-to-end flows\n5、Designing robust application architecture rather than only building prompt-based prototypes\n6、Python and modern software engineering practices\n7、LLM frameworks and orchestration approaches for agents, tools, retrieval, and workflow management, including tools such as LangGraph and similar agent orchestration frameworks\n8、RAG, embeddings, vector search, structured data retrieval, and context management\n9、LLM evaluation, testing, observability, prompt/version management, and production monitoring\n10、Managing reliability, latency, token usage, cost, security, and failure handling in production LLM applications\n三、Seniority Expectations\n1、We are specifically looking for someone at Senior Engineer level who can:\n2、Take ownership of a complex LLM use case with limited supervision\nTranslate a business problem into an appropriate technical design\n3、Make sound architectural decisions, including when to use agentic or multi-agent approaches versus simpler solutions\n4、Identify technical risks and trade-offs early\n5、Write maintainable, production-quality code\n6、Review and improve the work of other engineers where needed\n7、Collaborate effectively with Data Scientists, Engineers, Product/Business teams, and technical stakeholders\n8、Help raise the engineering quality of the team through good practices and technical judgement"
}