AI Engineer / Architect

Experience: 4 to 5 years

Location: Guangzhou (DTC)

Skills: Python, asyncio, FastAPI, LangGraph, CrewAI, AutoGen, LangChain, LlamaIndex, Google ADK, Claude SDK, model inference, Prompt Engineering, Tool/Function Calling, Model Context Protocol (MCP), Agentic Workflows, Docker, OpenShift

Job Responsibilities
1. Leadership & Stakeholder Management
Leadership: Act as the subject matter expert for Agentic engineering. Guide the overarching AI technology stack selection, system architecture design, and long-term engineering excellence.
User & Requirement Alignment: Collaborate closely with product management and end-users to translate complex business workflows and user needs into concrete multi-agent requirements.
Team Mentorship: Mentor and upskill engineering team members on LLM architectures, prompt engineering, asynchronous backend development, and AI engineering best practices.
2. Multi-Agent & LLM Engineering
Agent System Design: Design and deploy Agents from 0 to 1. Own the architecture design, Tool/Function Calling implementations, multi-Agent collaboration protocols, and complex Workflow orchestrations.
Framework Implementation: Leverage LLM ecosystems and SDKs to build robust corporate solutions using MCP and Agentic Workflows.
AI Evaluation: Build and construct automated evaluation pipelines to validate non-deterministic agent behaviors, optimize decision-making accuracy.
3. Backend & Distributed Systems Infrastructure
Production Services: Architect, develop, test, and deploy highly concurrent, high-availability, production-grade Web Services. Independently complete backend service infrastructure.




System Optimization: Build and optimize high-performance distributed systems, driving system performance optimization and engineering excellence across the entire stack.
DevOps & Deployment: Utilize containerization technologies like Docker and OpenShift to complete application deployment, scaling, and daily operations.

Job Requirements
1. Experience & Track Record
Experience: Approximately 10 years of skilled working experience.
AI Focus: The latest 4–5 years must be specifically dedicated to the AI domain, with a proven track record in LLM and Agent technologies.
Project Track Record: Must have 3+ years of hands-on AI-related experience, with active participation in at least 3 real-world production-grade deployment projects. At least 1 project must be a complex Multi-Agent, Agentic Workflow.
2. Technical Skills & Tech Stack
Languages & Core Backend: Expertise in Python, advanced asyncio, and FastAPI, with a proven track record of designing high-concurrency, high-availability backend architectures.
AI & Multi-Agent Frameworks: Hands-on proficiency with LangGraph, CrewAI, AutoGen, LangChain, LlamaIndex, Google ADK, and Claude SDK.
LLM Core & Protocols: Deep understanding of model inference, Prompt Engineering, Tool/Function Calling, Model Context Protocol (MCP), and Agentic Workflows.
DevOps & Infrastructure: Experience in distributed system development, building/maintaining complete CI/CD pipelines, and using containerization tools like Docker and OpenShift for deployment and operations.

Job
Data Technology
Schedule
Regular
Employee Status
Full time

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