西门子Solution Architecture Professional
社招全职5-10年信息技术地点:北京状态:招聘♡ 收藏
工作描述
Responsibilities ● Work with business units to identify AI use cases and gather requirements for LLM-powered applications. ● Design and deploy AI platform components — LLM Gateway (routing, API abstraction, quota & observability), RAG pipelines, prompt/agent orchestration, and AI application frameworks; evaluate alternatives and coordinate proofs of concept. ● Track the AI ecosystem and technology trends, and turn that insight into architecture and product decisions. ● Apply the AI platform to real-world use cases (e.g. enterprise search, document Q&A, code generation, AI-assisted forecasting). ● Ensure responsible AI: data security, model governance, cost control, and output quality. ● Build up the team's AI knowledge and skills. Required Knowledge/Skills, Education, and Experience ● Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or Physics. ● Deep understanding of…
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包括英文材料
大模型+
https://www.youtube.com/watch?v=xZDB1naRUlk
You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers.
https://www.youtube.com/watch?v=zjkBMFhNj_g
RAG+
https://www.youtube.com/watch?v=sVcwVQRHIc8
Learn how to implement RAG (Retrieval Augmented Generation) from scratch, straight from a LangChain software engineer.
Prompt+
https://cloud.google.com/vertex-ai/generative-ai/docs/learn/prompts/introduction-prompt-design
A prompt is a natural language request submitted to a language model to receive a response back.
https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/prompt-engineering
These techniques aren't recommended for reasoning models like gpt-5 and o-series models.
https://www.youtube.com/watch?v=LWiMwhDZ9as
Learn and master the fundamentals of Prompt Engineering and LLMs with this 5-HOUR Prompt Engineering Crash Course!
AI agent+
https://www.ibm.com/think/ai-agents
Your one-stop resource for gaining in-depth knowledge and hands-on applications of AI agents.
安全防护+
https://roadmap.sh/cyber-security
Step by step guide to becoming a Cyber Security Expert
https://www.w3schools.com/cybersecurity/
This course serves as an excellent primer to the many different domains of Cyber security.
学历+
Azure+
https://azure.microsoft.com/
Invent with purpose, realize cost savings, and make your organization more efficient with Microsoft Azure’s open and flexible cloud computing platform.
vLLM+
https://www.newline.co/@zaoyang/ultimate-guide-to-vllm--aad8b65d
vLLM is a framework designed to make large language models faster, more efficient, and better suited for production environments.
https://www.youtube.com/watch?v=Ju2FrqIrdx0
vLLM is a cutting-edge serving engine designed for large language models (LLMs), offering unparalleled performance and efficiency for AI-driven applications.
TGI+
https://huggingface.co/docs/text-generation-inference/en/index
Text Generation Inference (TGI) is a toolkit for deploying and serving Large Language Models (LLMs).
https://learn.ritual.net/examples/tgi_inference_with_mistral_7b
In this tutorial, we will use Huggingface's TGI (Text Generation Interface) API to query a Large Language Model (LLM) and enable users to requests jobs from it, both on-chain and off-chain.
https://www.sandgarden.com/learn/text-generation-inference-tgi
Text Generation Inference (TGI) is the process by which a trained AI model generates new text based on an input prompt, focusing on producing this text efficiently in terms of speed and computational resources.
LangChain+
https://python.langchain.com/docs/tutorials/
New to LangChain or LLM app development in general? Read this material to quickly get up and running building your first applications.
https://www.freecodecamp.org/news/beginners-guide-to-langchain/
LangChain is a popular framework for creating LLM-powered apps.
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