JD数据
{
"schema_version": "via_ai_product_manager_jobs_v1",
"data_type": "ai_product_manager_jobs",
"job": {
"job_title": "AI Agent / LLM应用工程师(郑州)(J13628)",
"job_level": "中级",AI生成
"work_category": "全职",AI生成
"department": "",
"location": "郑州·金水区·祭城",
"work_mode": "现场办公",AI生成
"job_category": "职责混合/无法判定"AI生成
},
"company": {
"company_name": "中科曙光",
"company_industry": "互联网",
"company_size": "1000-9999人",
"company_website": "",
"company_description": ""
},
"compensation": {
"salary_range": {
"min": 25000,
"max": 50000,
"currency": "CNY",
"cycle": "month"
},
"benefits": ""
},
"requirements": {
"working_years": 3,
"degree": "本科",
"language": "中英双语",AI生成
"visa_support": "",
"responsibilities": "",
"requirements_text": "工作职责:\n1.负责基于大模型(LLM)的 AI Agent 系统开发与应用落地。\n2.设计和实现RAG(检索增强生成)架构,构建企业知识库。\n3.开发和优化智能体⼯作流、多Agent协作、⼯具调⽤能力。\n4.进行Prompt Engineering、Agent策略优化与效果提升。\n5.参与模型训练或微调(LoRA / SFT)及推理优化。\n6.建⽴Agent评估体系,提升回答准确率和稳定性。\n任职资格:\n1.熟练掌握Python 或 Golang,具备良好的工程能力。\n2.熟悉LLM 应用开发与 AI Agent 架构。\n3.熟悉RAG 技术体系,有知识库构建经验。\n4.熟悉至少一种 Agent开发框架(LangChain / LlamaIndex / AutoGen / LangGraph 等)。\n5.熟悉向量数据库和检索系统(Milvus / FAISS / Qdrant 等)。\n6.有模型微调、Prompt Engineering 或 Agent评估经验优先。\n加分项\n1.有AI Agent平台或多Agent系统开发经验\n2.熟悉OpenClaw、Function Calling、Tool Use\n3.有LLM产品落地或企业知识库项目经验\n4.熟悉 Docker / Kubernetes / AI模型部署",
"skills": [AI生成
"AI数据安全与合规治理",
"API/SDK与开放平台开发",
"Agent系统构建",
"GTM与商业化策略",
"Linux/DevOps/CI-CD"
],
"preferred_qualifications": "",
"job_highlights": ""
},
"contact": {
"recruiter_name": "",
"contact_methods": [
{
"type": "apply_link",
"value": "https://www.zhipin.com/job_detail/61ae9c38c7b1ed440nd-3di_FVpT.html"
}
]
},
"posting": {
"posting_id": "61ae9c38c7b1ed440nd-3di_FVpT",
"post_date": "",
"hire_time": "",
"update_date": "",
"job_url": "https://www.zhipin.com/job_detail/61ae9c38c7b1ed440nd-3di_FVpT.html"
},
"fulltext": "工作职责:\n1.负责基于大模型(LLM)的 AI Agent 系统开发与应用落地。\n2.设计和实现RAG(检索增强生成)架构,构建企业知识库。\n3.开发和优化智能体⼯作流、多Agent协作、⼯具调⽤能力。\n4.进行Prompt Engineering、Agent策略优化与效果提升。\n5.参与模型训练或微调(LoRA / SFT)及推理优化。\n6.建⽴Agent评估体系,提升回答准确率和稳定性。\n任职资格:\n1.熟练掌握Python 或 Golang,具备良好的工程能力。\n2.熟悉LLM 应用开发与 AI Agent 架构。\n3.熟悉RAG 技术体系,有知识库构建经验。\n4.熟悉至少一种 Agent开发框架(LangChain / LlamaIndex / AutoGen / LangGraph 等)。\n5.熟悉向量数据库和检索系统(Milvus / FAISS / Qdrant 等)。\n6.有模型微调、Prompt Engineering 或 Agent评估经验优先。\n加分项\n1.有AI Agent平台或多Agent系统开发经验\n2.熟悉OpenClaw、Function Calling、Tool Use\n3.有LLM产品落地或企业知识库项目经验\n4.熟悉 Docker / Kubernetes / AI模型部署"
}