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Binance - AI Agent Engineer

Hong Kong; Singapore2d ago

In Office Mid APAC Artificial Intelligence AI Engineer Product Marketing Digital Marketing Java Python Vector Data Analysis Governance Redis Elasticsearch Kafka

Requirements

• 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. • 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.

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.

Benefits

• Shape the future of finance • Collaborate with world-class talent in a user-centric global organization with a flat structure • Tackle challenging projects in a fast-paced and innovative enviornment with autonomy • Thrive in a results-driven workplace with opportunities for career growth and continuous learning • Competitive salary and company benefits • Remote-first, work-from-home arrangement (may vary depending on the nature of the role and team)