2 months ago
Guangzhou, ChinaStaff+
Responsibilities
- Lead architecture, technical direction, and implementation for an enterprise-grade knowledge intelligence and RAG platform.
- Design and build scalable capabilities for ingestion, extraction, enrichment, classification, knowledge asset management, discovery, reuse, governance, and downstream consumption.
- Lead workflows for refining, summarizing, classifying, deduplicating, consolidating, and contextualizing fragmented information into trusted knowledge assets.
- Architect ontology and taxonomy management, entity and relation extraction, entity resolution, graph modeling, graph traversal, lineage-aware context assembly, and graph-based reasoning.
- Establish knowledge ownership, validation, versioning, publishing, freshness monitoring, deprecation, retention, rollback, quality scoring, duplication detection, contradiction detection, and provenance validation.
- Define SLOs and SLAs, observability, alerting, capacity planning, cost controls, incident response, troubleshooting playbooks, resilience patterns, and continuous production improvement.
- Partner with AI engineering, data platforms, cybersecurity, architecture, product, and domain subject-matter teams; mentor engineers and review designs.
Requirements
- Bachelor’s or master’s degree in computer science, software engineering, information management, data engineering, AI, or a related technical discipline.
- At least 7 years of hands-on engineering experience in backend, data, AI, knowledge, search, or enterprise information platforms.
- Experience as a senior technical IC or platform technical lead owning architecture, engineering standards, design reviews, implementation quality, optimization, and production readiness.
- Deep knowledge of taxonomy and ontology design, metadata standards, knowledge refinement, lifecycle management, governance, lineage, and enterprise content operations.
- Hands-on experience with knowledge graphs, semantic search, RAG, agentic AI, or data enrichment systems.
- Strong engineering foundations in distributed systems, APIs, data pipelines, observability, CI/CD, Docker, and Kubernetes.
- Ability to apply security, compliance, production, stakeholder, mentoring, cross-functional influence, and AI-native practices.
Benefits
- Flexible working and opportunities for continuous professional development and career growth.
- Inclusive and diverse workplace with equal-opportunity employment practices.
- Location: Guangzhou or Xi’an.
Tech Stack
Categories
BackendData Engineering
About HSBC
HSBC is a global bank that provides retail, commercial and investment banking, payments, and wealth management to individuals, SMEs, and multinationals. It earns fees, interest income, and trading revenues through branches and digital platforms across major markets. Headquartered in London, it serves over 40 million customers in 58 countries and is listed in London, Hong Kong, New York, and Bermuda.