AI 全栈工程师（AI Agent 方向）
岗位职责
负责 AI 产品从 0 到 1 全流程落地，聚焦 AI Agent 与 RAG 系统的工程化开发，践行 “工程化驾驭大模型” 的 Harness Engineer 理念，支撑业务场景智能化升级。 主导 AI Agent 架构设计与开发：基于 LangGraph/LangChain/AgentScope/Google-ADK 实现工作流编排、工具链开发、多 Agent 协作及 Human-in-the-Loop 交互，完成复杂任务自动化与智能决策落地。 构建并优化端到端 RAG 系统：负责文档解析、分块、向量化、多路检索、重排序全流程设计，结合上下文工程（Query Rewrite、动态 Prompt、对话历史管理）提升大模型推理质量。 实现大模型工程化落地：完成多模型集成调度、流式输出、提示词工程优化，将 AI 能力与业务场景深度融合。 搭建高可用后端服务：基于 Python（FastAPI/Flask）或 Go（Gin）开发 API 与业务逻辑层，精通异步编程与微服务架构，保障系统稳定性与性能。 负责项目部署运维与架构优化：基于 Docker/K8s 完成容器化部署，搭建 CI/CD 流程，保障项目高效迭代与稳定运行。 对接业务团队，拆解需求并转化为技术方案，参与技术选型与架构优化，沉淀最佳实践并推动团队技术能力提升。
任职要求
本科及以上学历，计算机 / 人工智能等相关专业，3 年及以上 AI 相关或全栈开发经验，有 AI 产品落地经验优先。 精通 AI Agent 工程化开发：熟练使用 LangGraph/LangChain/AgentScope/Google-ADK，具备工作流编排、工具链开发、多 Agent 协作及对话状态管理的落地经验。 具备扎实的 RAG 与上下文工程能力：熟悉文档解析、向量数据库（Milvus/FAISS 等）、多路检索、Reranker 优化，掌握 Query Rewrite、动态 Prompt、对话历史压缩等优化手段。 熟练掌握大模型工程化技术：提示词工程、多模型调度（Azure OpenAI / 通义千问等）、流式输出，了解模型微调优先。 后端开发能力：精通 Python（FastAPI 优先），熟悉异步编程、微服务架构；了解 Spring AI/Spring Boot 者优先。 熟悉前端开发基础（Vue/React）、容器化部署（Docker/K8s）及 CI/CD 流程，能独立完成项目全流程交付。 具备良好的需求拆解与问题排查能力，关注 AI 前沿技术，能推动业务场景的技术创新与优化。
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