Wei Yang

Production AI, search, CMS, and personalization for industrial digital platforms.

• Built production RAG conversational AI and hybrid-search experiences with Azure OpenAI, Redis, and Weaviate
• Designed recommendation and offline ML pipelines for personalization, funnel optimization, and targeting
• Integrated partner/location CRM updates via MuleSoft into Solr and Elasticsearch with caching
• Developed licensed AEM CMS software for content authoring and publishing, integrating with search, PIM, marketing, and ecommerce platforms
• Translated business and UX requirements into modular, decoupled components; maintained data stores, documentation, and QA for reliable operations
• Hardened delivery with secure AI workflows, multilingual retrieval, and maintainable cross-system data flows

Deep learning and NLP engineering for financial text analysis.

• Built and maintained data-processing and training workflows for NLP experiments on financial text
• Modularized pipelines and PyTorch/ML helpers into reusable utils for shared research use
• Set up and operated remote Ubuntu GPU environments for deep learning training and evaluation
• Supported language-feature and text-classification studies with domain-adapted BERT models

AI content transformation — PDFs become semantic HTML and structured AEM components for enterprise publishing.

• Delivered PDF-to-semantic-HTML workflows that produce authored Adobe Experience Manager components
• Implemented an agentic LLM-vision pipeline to parse layout and generate reusable AEM components
• Added I18N translation support governed by brand voice and editorial guidelines

Agentic AI conversation platform — playbooks and tools for knowledge-grounded marketing-funnel optimization.

• Contributed to POC development and architecture recommendations for knowledge ingestion, retrieval, agentic playbooks, internal tools, and conversation flows
• Researched and optimized response grounding, routing, and funnel-oriented system behavior

Real-time AI search overview — hybrid retrieval across heterogeneous enterprise sources.

• Built real-time search overview and autosuggest with live-query caching for low-latency responses
• Engineered multilingual indexing across 10+ sources with hybrid search, reranking, routing, and iterative retrieval
• Added reporting pipelines and feedback loops to improve overview relevance and quality over time

Agentic conversational AI — enterprise website support chat with internal company tools.

• Built an agentic chatbot with Azure OpenAI, Redis, and Weaviate, integrating internal company tools and APIs through function calling
• Designed multi-turn Redis memory and agentic function-calling workflows for tools and APIs
• Implemented security guardrails including input sanitization, content filtering, and PII masking

Recommendations and offline ML — behavioral data turned into personalized product experiences.

• Built user-to-item and item-to-item recommendation pipelines with rolling cache and Akamai CDN
• Designed offline ML pipelines for interaction modeling, personalization, and user classification
• Improved sales-funnel conversion and marketing targeting through customized product experiences

AI-assisted technical support — fault-code lookup across industrial product documentation.

• Built AI-assisted lookup of condition, event, and fault codes across industrial product families
• Connected product-family selection and code queries to Technical Documentation Center retrieval
• Delivered production troubleshooting access for drives, controllers, and motion systems

CRM-to-search data integration — partner and location records made reliably discoverable.

• Designed 7+ MuleSoft API workflows for incremental CRM delta updates of partner accounts and locations
• Integrated multi-source records into Lucidworks Solr and Elasticsearch search with cache optimization
• Improved reliability of partner and location data for searchable enterprise applications

面向工业数字平台的生产级 AI、搜索、CMS 与个性化。

• 使用 Azure OpenAI、Redis 与 Weaviate 构建生产级 RAG 对话式 AI 与混合搜索体验
• 设计用于个性化、漏斗优化与定向的推荐与离线 ML 流水线
• 通过 MuleSoft 将合作伙伴/地点 CRM 更新集成到 Solr 与 Elasticsearch，并配合缓存
• 开发可授权的 AEM CMS 软件，用于内容创作与发布，并与搜索、PIM、营销与电商平台集成
• 将业务与 UX 需求转化为模块化、解耦组件；维护数据存储、文档与 QA，保障可靠运维
• 通过安全 AI 工作流、多语言检索与可维护的跨系统数据流强化交付

面向金融文本分析的深度学习与 NLP 工程。

• 构建并维护面向金融文本 NLP 实验的数据处理与训练工作流
• 将流水线与 PyTorch/ML 辅助工具模块化为可复用 utils，供研究共享使用
• 搭建并运维远程 Ubuntu GPU 环境，用于深度学习训练与评估
• 以领域自适应 BERT 模型支持语言特征与文本分类研究

AI 内容转换——将 PDF 转为语义 HTML 与结构化 AEM 组件，用于企业发布。

• 交付 PDF 到语义 HTML 工作流，生成可编辑的 Adobe Experience Manager 组件
• 实现智能体 LLM-vision 流水线以解析版面并生成可复用 AEM 组件
• 增加受品牌语气与编辑规范约束的 I18N 翻译支持

智能体 AI 对话平台——面向知识 grounding 营销漏斗优化的 playbook 与工具。

• 参与 POC 开发，并就知识摄入、检索、智能体 playbook、内部工具与对话流程提供架构建议
• 研究并优化回答 grounding、路由与面向漏斗的系统行为

实时 AI 搜索概览——跨异构企业数据源的混合检索。

• 构建实时搜索概览与自动建议，含实时查询缓存以实现低延迟响应
• 工程化跨 10+ 数据源的多语言索引，含混合搜索、重排序、路由与迭代检索
• 增加报表流水线与反馈闭环，持续改进概览相关性与质量

智能体对话式 AI——集成内部公司工具的企业网站支持聊天。

• 使用 Azure OpenAI、Redis 与 Weaviate 构建智能体聊天机器人，通过函数调用集成内部公司工具与 API
• 设计多轮 Redis 记忆与面向工具/API 的智能体函数调用工作流
• 实现安全护栏，包括输入净化、内容过滤与 PII 掩码

推荐与离线 ML——将行为数据转化为个性化产品体验。

• 构建用户到物品与物品到物品推荐流水线，含滚动缓存与 Akamai CDN
• 设计用于交互建模、个性化与用户分类的离线 ML 流水线
• 通过定制化产品体验提升销售漏斗转化与营销定向

AI 辅助技术支持——跨工业产品文档的故障代码查询。

• 构建跨工业产品系列的条件、事件与故障代码 AI 辅助查询
• 将产品系列选择与代码查询连接到技术文档中心检索
• 为驱动器、控制器与运动系统交付生产级排障访问

CRM 到搜索数据集成——使合作伙伴与地点记录可靠可发现。

• 设计 7+ 个 MuleSoft API 工作流，用于合作伙伴账户与地点的 CRM 增量更新
• 将多源记录集成到 Lucidworks Solr 与 Elasticsearch 搜索，并优化缓存
• 提升合作伙伴与地点数据在可搜索企业应用中的可靠性