AI Agent Engineer

Team: Big Data

Location: Asia, Hong Kong

Commitment: Full-time Onsite or Remote

Workplace Type: hybrid

Responsibilities

• Develop an enterprise-grade conversational agent platform to support core business scenarios such as AI search, token insight conversations, trading assistant Q&A, and trading strategy generation.
• Design and implement multi-turn conversation capabilities, including contextual memory, tool calling and orchestration, clarification and follow-up questioning, and fallback handling, to create a natural and coherent conversational experience.
• Build and optimize the large-model application pipeline, including prompt engineering, retrieval-augmented generation (RAG), tool calling / function calling, and workflow orchestration.
• Work closely with product, algorithm, data, and trading teams to deploy conversational AI capabilities into real business scenarios and continuously drive iterative improvements.
• Establish quality monitoring and evaluation systems for production environments, continuously improving key metrics such as first-resolution rate, conversation completion rate, response latency, and user satisfaction.
• Ensure system stability, security, and compliance, while continuously improving performance, availability, and observability under high-concurrency scenarios.

Qualifications

• Master’s degree or above in Computer Science or a related field is preferred.
• More than 2 years of backend development experience, with solid engineering skills in Java or Python and familiarity with common microservices architectures.
• Hands-on experience in deploying large-model / AI applications, with a deep understanding of key technologies such as prompt engineering, RAG, vector retrieval, and function calling.
• Strong complex system design capabilities, with familiarity in caching, message queues, databases, and service governance.
• Strong interest in digital asset trading, market structure, on-chain data, and token-related information, with a willingness to deeply understand trader needs and behaviors.
• Strong data analysis and troubleshooting skills, with the ability to drive continuous system improvement based on logs and metrics.
• Strong cross-functional communication and project execution skills, with a results-oriented mindset.
• Preferred Qualifications
  Experience in AI search, financial information retrieval, or token / project research products.
  Experience with trading products, market analysis, quantitative tools, or strategy platforms.
  Experience building agent platforms, A/B testing frameworks, or evaluation datasets.
  Familiarity with technologies such as Redis, Kafka, Elasticsearch, and vector databases.