First VP/VP, GenAI Knowledge Layer Specialist, Innovation Group

UOB•Phoenix, AZ

26d

About The Position

United Overseas Bank Limited (UOB) is a leading bank in Asia with a global network of more than 500 branches and offices in 19 countries and territories in Asia Pacific, Europe and North America. In Asia, we operate through our head office in Singapore and banking subsidiaries in China, Indonesia, Malaysia and Thailand, as well as branches and offices. Our history spans more than 80 years. Over this time, we have been guided by our values – Honorable, Enterprising, United and Committed. This means we always strive to do what is right, build for the future, work as one team and pursue long-term success. It is how we work, consistently, be it towards the company, our colleagues or our customers. Key responsibilities: The GenAI Knowledge Layer Specialist establishes enterprise knowledge foundations—semantic models, graphs, and governance—that ground AI with trusted information. The role will design and maintain the semantic and knowledge foundations that allow AI to operate with trusted, contextual information. The Knowledge Specialist will be instrumental in ensuring that knowledge assets are structured, governed, and optimised for AI adoption across domains.

Requirements

Proven track record of delivering impact in AI-enabled transformation programs.
10-15 years experience in data engineering, data integration, ETL processes, and metadata management
Strong understanding of semantic layer or technologies such as data fabric
Ability to collaborate across cross-functional teams and stakeholders.
Strong problem-solving skills and adaptability in fast-changing environments.
Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, or related fields

Nice To Haves

Experience with knowledge graph design and implementation a plus
Familiarity with vector databases
Prior experience in financial services is highly desirable

Responsibilities

Knowledge Architecture Design enterprise knowledge structures to enable precise retriewval and reuse.
Define taxonomies, ontologies, and metadata for cross‑domain interoperability.
Ensure knowledge assets are secured, versioned, and discoverable.
Produce and maintain data products catalogue with clear ownership, quality, and traceability.
Semantic Layer & Knowledge Graph Develop semantic models and knowledge graph patterns that ground AI reasoning.
Optimise chunking, embeddings, and retrieval strategies for RAG use cases.
Establish quality checks to reduce hallucinations and improve precision.
Design and evolve semantic models/knowledge graphs for accurate retrieval.
Content Lifecycle & Search Operationalise content ingestion, curation, and expiry processes.
Improve findability with search tuning, synonyms, and feedback loops.
Measure usefulness and drive continuous optimisation of content assets.
Knowledge Governance Define ownership, access, and approval workflows for key knowledge assets.
Ensure compliance with privacy, security, and copyright requirements.
Run periodic reviews and cleanup to maintain integrity and value.