轉職熱搜工作

【Job Overview】 We are seeking an expert AI Platform & Agent Architect to lead the design, implementation, and operationalization of GPU-based LLM infrastructure, secure AI Gateway systems, and orchestrated multi-agent workflows. This role entails building AI Gateways to route and govern model/tool access, operating MCP servers, enabling multi-agent collaboration, designing RAG pipelines, and establishing robust LLMOps/MLOps practices. 【Responsibilities】 1. Design and manage GPU-powered LLM inference platforms (e.g. vLLM, Triton) on Kubernetes with CI/CD, monitoring, and resource optimization. 2. Architect and deploy a scalable AI Gateway layer for secure, efficient, fallback-capable model and tool access with observability and rate limiting. 3. Develop and maintain MCP servers, including defining tools/resources, implementing JSON‑RPC session flows and context negotiation per MCP specs. 4. Build multi‑agent orchestration frameworks using MCP, coordinating context exchange, tool usage, session management, and shared memory. 5. Design and implement RAG pipelines using vector databases ( e.g., FAISS, Qdrant, Chroma) to augment agent workflows. 6. Establish LLMOps & MLOps best practices: model versioning, GPU utilization tracking, CI/CD pipelines, and observability (leveraging OpenTelemetry for metrics, traces, and logs). 7. Integrate enterprise-grade authentication (SSO/OAuth) and enforce governance, context-level access control across Gateway and MCP layers. 【Basic Qualifications】 1. Proven experience building AI Gateways: secure routing, token management, failover, rate limit, and observability. 2. Hands-on with MCP server/client architecture: context specification, JSON-RPC session handling, tool negotiation. 3. Strong track record designing multi-agent systems with coordinated tool use and shared context delivery. 4. Expert knowledge in GPU-based LLM inference and orchestration (Kubernetes, CI/CD, inference engines). 5. Experience building Retrieval-Augmented Generation pipelines and integrating vector databases. 6. Solid LLMOps/MLOps background—model lifecycle management, observability, deployment automation. 7. Excellent collaboration and communication skills for cross-functional system architecture work. 【Preferred Qualifications】 1. Familiarity with security and governance for MCP/gateway layers: session scoping, prompt injection mitigation, permission modeling. 2. Proven skills in prompt engineering, model fine-tuning, and inference optimization. 3. Prior experience building internal AI platforms or model registries.

1 .三年以上開發經驗(具備LLM、RAG Architecture、網路爬蟲) 2. 熟悉以下領域的技術：Python、TensorFlow、LLM、LangChain framework、RAG architecture、Embedding、File ingestion。 (Option)3. 熟悉 MsSQL/Oracle資料庫與API整合開發。 (Option)4. 熟悉 linux(x86/arm-base)/docker 5. 其他主管交辦事項

1.負責績效指標資料的收集及預算支用進度之管制。 2.執行數據收集與分析，進行成果評估與研究撰寫 3.彙整成果資料，協助完成期中/期末報告(B2-社區醫療群)。 4.協助研究計畫進行及處理相關行政工作（如文件管理、經費核銷等作業）。

協助處理MIS專員工作事項 受資訊長督導，與廠區進行專案改善計劃並追蹤掌握進度 有以下經驗者佳： PHP/SQL 開發 Microsoft Sql Server管理 Microsoft Visul C# 開發 網管/資安相關 與量產工廠溝通

協助處理MIS專員工作事項 獨立主導開發廠區專案改善計劃 有以下經驗者佳： PHP/SQL 開發 Microsoft Sql Server管理 Microsoft Visul C# 開發 網管/資安相關 與量產工廠溝通

1. 資訊安全及相關文件管理作業。 2. 協助資訊設備問題排除處理。 3. 協助請修/儀器/硬體系統管理。 4. 協助行政庶務(收發公文、信件等)。 5. 會議臨時支援事項。 6. 主管交辦事項。 工作技能： 1. 文件收發與檔案管理 2. 行政事務處理 3. 電腦設備裝配 4. 系統維護操作 5. 網路設備設定安裝 ※有醫院相關經驗核發經驗薪，並優先錄取

擇一 1.AI視覺應用開發(文件辨識、影像畫質強化、物件追蹤、自主定位) 2.多感測器整合(sensor fustion)技術開發 2.智能化無人載具(無人機、無人車)技術整合/控制 3.大型語言模型(LLM)新興應用開發與研究(科學計算、圖像/文字精準搜索) ★實習表現優異，將優先預聘。 ★提供免費多元自主學習平台(天下創新學院、哈佛商業評論等多達兩千門精選課程)。