About the role
We are looking for a forward-thinking AI Engineer who doesn't just build chatbots, but designs autonomous agents. In this role, you will move beyond simple RAG (Retrieval-Augmented Generation) to develop agentic workflows capable of reasoning, planning, and executing complex business tasks. You will leverage the AWS ecosystem to build scalable, secure, and production-grade AI systems that integrate directly with the core business operations.
About the job
- Design and implement multi-agent systems using frameworks like LangGraph, AutoGen, or CrewAI to automate end-to-end business processes.
- Build sophisticated reasoning loops (Chain-of-Thought, ReAct) that allow agents to use tools, call APIs, and self-correct.
- Deploy and scale models using Amazon Bedrock, Amazon SageMaker, and AWS Lambda.
- Implement advanced RAG pipelines utilizing Amazon Kendra or Vector Engine for Amazon OpenSearch to provide agents with real-time business context.
- Establish rigorous testing frameworks to measure agent reliability, hallucination rates, and cost-efficiency.
- Partner with product and operations teams to identify manual bottlenecks that can be solved through autonomous AI agents.
Requirements
- Bachelor of Computer seience, information system, or equaivalent
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Deep understanding of LLMs (Claude, Llama, GPT) and the nuances of prompt engineering for tool-calling.
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Mastery of Python and experience with asynchronous programming (essential for agentic loops).
- Hands-on experience with AWS (IAM, S3, Bedrock, Step Functions, and EventBridge).
- Experience with vector databases for long-term agent memory and context retrieval.
- Familiarity with CI/CD for AI, including monitoring agent traces and performance logging.
- Proficient in Chinese and English
Application
Our specialist consultant Wendy will get in touch with you soon, if we find your profile suitable for this position or any other vacancies we are recruiting for.
