AI Engineer Agentic AI & Customer Service Automation

Key Responsibilities

• Design, build, and deploy AI Agents and agentic workflows for Customer Service and operational use cases, covering reasoning, decision-making, tool calling, and multi-step task execution.
• Develop production-ready LLM applications, including prompt engineering, structured outputs, function/tool calling, context management, and LLM orchestration.
• Build and optimize RAG and knowledge retrieval solutions, improving retrieval quality, grounding, knowledge accuracy, and AI response quality.
• Develop AI-driven intent classification, decision logic, and intelligent routing, determining when requests should be handled by AI, automation, or human agents.
• Integrate AI solutions with CRM, Zendesk, APIs, internal platforms, and automation/workflow systems, enabling agents to retrieve information and trigger approved actions.
• Establish evaluation and monitoring frameworks covering accuracy, hallucination, retrieval quality, task completion, latency, cost, and business outcomes.
• Own AI use cases end-to-end—from identifying business problems and building PoCs to integration, production deployment, monitoring, and continuous improvement.
• Partner closely with Customer Service, Automation, CRM, Product, and Engineering teams to translate operational pain points into scalable AI solutions.

Requirements

• Bachelor's degree in Computer Science, AI, Data Science, Software Engineering, or a related discipline, with 3+ years of relevant software engineering, AI/ML, or Applied AI experience.
• Strong hands-on Python development skills with experience building backend services or AI applications using FastAPI or similar frameworks.
• Practical experience with LLMs, prompt engineering, RAG, embeddings/vector search, function/tool calling, and LLM evaluation.
• Experience building AI Agents or agentic workflows and working with agent orchestration frameworks; MCP or similar tool-integration experience is advantageous.
• Strong understanding of REST APIs, JSON, authentication, system integration, Docker/cloud deployment, CI/CD, and production monitoring.
• Proven ability to independently take AI solutions from business problem → prototype → integration → production, with a strong focus on measurable business impact.
• Excellent communication and presentation skills, with proficiency in both English and Chinese to effectively engage regional Chinese-speaking stakeholders.

Preferred Experience

• Experience with Customer Service AI, chatbots, Zendesk/Salesforce/CRM platforms, workflow automation, AI quality evaluation, or FinTech/financial services environments would be advantageous.