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中国移动 is seeking a senior lead to design core technical architecture for large model platforms and AI applications. You will drive high-concurrency, microservice-based systems, and build workflow engines to orchestrate prompts, agents, tools, APIs, and business systems.
You will oversee major projects, set agile plans, and stay abreast of open-source developments in LangChain, LlamaIndex, and vLLM to reduce costs and boost efficiency.
Lead the core technical architecture design of large model platforms and AI applications, deliver key project milestones, and integrate with external AI ecosystems (vendors / open-source communities). Build high-performance workflow engines and model scheduling systems to ensure the platform supports high concurrency, high availability, multi-model compatibility and fast delivery.
Design the architecture for large model middle platform / Agent platform (including Gateway, Routing, RAG, Cache modules), and lead capability building and technology selection for PaaS/SaaS-grade AI platforms.
Oversee major technical projects related to enterprise large models, formulate agile development plans, conduct core technology research, and control full-lifecycle schedule and code quality.
Drive R&D of low-code / no-code AI workflow engines (Workflow Engine), enabling flexible orchestration across Prompt, Agent, Tools, APIs and various business systems.
Manage integrations with external large model vendors (API connection, private cloud deployment), track latest developments in open-source communities such as LangChain, LlamaIndex and vLLM, and introduce cutting-edge technologies to reduce costs and boost efficiency.
5 years or above relevant working experience
Bachelor’s degree or above in Computer Science, Communication Engineering, IT, Software Engineering, Information Security, Big Data, Artificial Intelligence or related disciplines.
Expertise in high-concurrency and microservice architecture; hands-on experience with Kubernetes ecosystem and GPU computing resource scheduling is preferred.
Familiar with at least one workflow / rule engine; proficient in LLM API calling mechanisms, streaming transmission (SSE) and Function Calling.
Hands-on experience deploying and accelerating inference for mainstream open-source LLMs (Kimi, Deepseek, Llama, Qwen). Experience with vLLM, TensorRT-LLM is a strong plus.
Strong governance awareness, pursuit of elegant code and high system availability, with excellent cross-team collaboration capabilities.