Senior Financial AI Engineer (Data & Knowledge Engineering)

Binance; Hong Kong; On-site; HKD 900,000 - 1,800,000; Full time

Benefits offered by this job

Competitive salary

Work-from-home

Career growth

Autonomy

Job summary

Binance in Hong Kong seeks a senior specialist to build production-grade AI data processing and knowledge services for the equities business. You will transform announcements, earnings, transcripts, and reports into data usable by trading products and Binance AI.

You will own end-to-end pipelines, knowledge bases, and RAG services, integrating LLMs and NLP models while ensuring traceability, performance, and cost governance in a fast-paced, global environment.

Qualifications

• Master’s level degree in CS/AI or related field with 5+ years in backend/data platforms/ML.
• Experience with equity markets and investor workflows; strong software engineering.
• Proficiency in Python and at least one backend language; distributed systems skills.
• Production experience with LLM/NLP/ML systems and knowledge engineering or RAG.

Responsibilities

• Own production-grade AI data processing pipelines for financial content, including text, tables, layout, and media.
• Build layered knowledge bases with source docs, facts, entities, events, and indices.
• Operate RAG services with multi-route retrieval, reranking, and citation.
• Design extensible frameworks with versioning, updates, and authorization control.
• Integrate LLMs, document understanding models, and NLP components into pipelines.
• Own APIs, async tasks, queues, caching, retries, and fault recovery for data processing.
• Establish QA systems for parsing accuracy, coverage, citation, latency, and cost.
• Collaborate with data, algorithm, product, and compliance teams for production use.

Skills

Python

Java

LLMs/NLP

Distributed systems

Education

Master's degree or above in CS/AI

Tools

Full-text search

Vector search

Document storage

Job description

Binance is a leading global blockchain ecosystem behind the world's largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products.

Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.

Role Overview

You will be responsible for production-grade AI data processing and knowledge services for Binance's equities business. You will transform financial information-announcements, news, earnings reports, earnings call transcripts and audio/video, research reports, and more-into data, knowledge, and evidence that trading products and Binance AI can directly consume. Knowledge engineering, knowledge bases, and retrieval-augmented generation (RAG) are the core scenarios. You will also build reusable processing frameworks and own model and rule integration, task orchestration, servitization, quality control, cost management, and production stability-not just document parsing, vectorization, or model API calls.

Responsibilities

• Own production-grade AI data processing pipelines for financial content (announcements, news, financial reports, earnings call materials, research reports, etc.), covering text, table, layout, and audio/video processing, as well as chunking, deduplication, clustering, standardization, versioning, and result validation.
• Build layered financial knowledge bases that manage source documents, structured facts, entities and events, full-text and vector indices, and relationship data; maintain metadata including source, time, security, market, language, version, and authorization.
• Engineer and operate RAG services in production-building query processing, permission and time filtering, multi-route retrieval, reranking integration, context assembly, evidence citation, and result return pipelines that ensure traceability to original sources.
• Design extensible AI data processing, knowledge engineering, and indexing frameworks with unified interfaces to adapt to new sources, formats, languages, models, rules, and algorithms; support incremental updates, index rebuilds, historical backfill, deletion, and authorization expiry.
• Integrate LLMs, document understanding models, NLP models, rule systems, and algorithm components into a unified pipeline with clear input/output contracts, task orchestration, version governance, and failure handling.
• Own engineering capabilities for AI data processing and knowledge services: APIs, async tasks, queues, caching, retry and graceful degradation, human review, canary releases, rollbacks, fault recovery, and capacity governance.
• Establish a quality system for AI data processing, knowledge, and RAG-measuring parsing accuracy, retrieval coverage, citation completeness, staleness, latency, stability, and cost, with tiered root-cause analysis.
• Collaborate with data, algorithm, product, and compliance teams to deploy AI data processing and knowledge services reliably in user-facing equities products and Binance AI.

Requirements

• Master's degree or above in Computer Science, Software Engineering, AI, or a related field; 5+ years of experience in backend, data platforms, ML engineering, or AI application engineering.
• Familiarity with equity markets and the investor research and decision-making workflow; understanding of trading mechanics, market data, fundamentals, corporate actions, and major market events; ability to assess the entities, time sensitivity, sources, and usage boundaries of financial information.
• Proficient in Python and at least one of Java or another backend language; solid software engineering, distributed systems, and service interface design skills.
• Production experience with LLMs, NLP, or ML systems; ability to explain model invocation, task orchestration, failure recovery, version governance, and online issue resolution.
• Production experience with knowledge engineering or RAG systems; familiarity with structured, semi-structured, and unstructured content processing; ability to explain the full pipeline from source ingestion through retrieval, citation, and online feedback.
• Familiarity with full-text search, vector search, document storage, and their combinations; understanding of chunking, indexing, filtering, recall, reranking, context assembly, citation, and permission control-not tied to any specific database or framework.
• Experience with performance, stability, cost, and observability governance for high-concurrency or large-scale processing systems-beyond model API calls or demo prototypes.
• Experience adapting new data sources or content types; ability to distill source-specific logic into reusable processing capabilities.

Why Binance

• Shape the future with the world's leading blockchain ecosystem
• Collaborate with world-class talent in a user-centric global organization with a flat structure
• Tackle unique, fast-paced projects with autonomy in an innovative environment
• Thrive in a results-driven workplace with opportunities for career growth and continuous learning
• Competitive salary and company benefits
• Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)

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