aimlroles

Applied AI Engineer / Architect

Dbs Open · verified Oct 22, 2026
Guangzhou Full-time Mid-level AI Engineering

At a glance

Mid-level AI Engineering role at Dbs. Guangzhou · full-time.

Pay not stated Applied AI Engineer salary

RoleAI Engineering
SeniorityMid-level
LocationGuangzhou
EmploymentFull-time
PostedJul 21, 2026 · 3mo ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Set the agent engineering direction, choosing the AI stack and shaping architecture for long-term reliability
  • Turn product and end-user workflows into multi-agent requirements, then design and launch agent systems
  • Build tool-calling, agent collaboration and workflow orchestration with MCP and agent frameworks
  • Create automated checks for agent behavior and improve decision accuracy
  • Develop and operate high-availability backend services and distributed systems, including container-based deployments

What you bring

  • Around ten years of professional experience, including the most recent four to five years focused on AI
  • At least three years of hands-on AI work across three or more production deployments, including a complex multi-agent project
  • Strong Python, asyncio and FastAPI skills, with experience designing high-concurrency backend systems
  • Practical ability with LangGraph, CrewAI, AutoGen or another listed agent framework, plus LLM protocols and tooling
  • Experience building distributed systems and CI/CD pipelines, and deploying with Docker, OpenShift or another listed platform

Who this fits

This role suits an experienced AI engineer who can own agent architecture and production backend systems while mentoring other engineers. The position is based in Guangzhou and is a regular full-time employee role.

From the employer

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 professional 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.

Location:

Guangzhou (DTC)

Job:

Data Technology

Schedule:

Regular

Employee Status:

Full time