Help shape how HSBC defines, organises and connects business terms across the Group by building high-quality glossaries, taxonomies and ontologies to create a shared semantic layer for AI use.
Responsibilities
Drive high-quality content within the HSBC Business Information Model (HBIM)
Curate and maintain coherent taxonomies and authoritative definitions
Support the Group ownership operating model
Contribute to ontology development to enable AI querying and reasoning
Apply industry standards (SKOS, PROV-O, DCAT, OWL Time, ORG, Dublin Core; FIBO/BIAN)
Requirements
Nice to have: Collibra experience
Nice to have: Python
Nice to have: APIs and automation/integration thinking
The Semantics Engineer (Ontologist) plays a critical role in designing and maintaining the enterprise information architecture essential for cataloging KeyBank’s data for self‑service understanding and enabling AI‑ready data and knowledge usage.
Compensation
This position is eligible to earn a base salary in the range of $96,000.00 - $181,000.00 annually. Compensation for this role also includes eligibility for incentive compensation which may include production, commission, and/or discretionary incentives.
Responsibilities
Lead the development and maintenance of the enterprise data domain model, taxonomy, and ontologies to ensure shared understanding, semantic consistency, and discoverability of data and knowledge assets.
Design and evolve information and semantic models that make enterprise data AI‑ready, supporting use cases ranging from traditional analytics and BI to applied machine learning and LLM‑based experiences (e.g., search, retrieval‑augmented generation, and copilots).
Operationalize data models, taxonomies, and semantic structures through the Enterprise Data Catalog (Alation).
Define and enforce standards for data modeling, taxonomy, nomenclature, and semantic structures to ensure consistency and interoperability across business domains and downstream consumption patterns.
Provide authoritative guidance on semantic conflicts—resolve definition discrepancies, harmonize terms, and mediate cross‑domain dependencies to establish trusted, reusable business meaning.
The Knowledge Asset Manager is responsible for the ongoing stewardship, governance, quality, and maintenance of the shared knowledge and data assets that support AI-enabled sourcing and procurement capabilities.
Responsibilities
Own and govern shared knowledge and data structures
Design and maintain ontology models
Define and manage taxonomy, classification schemas, metadata structures, and semantic models
Act as gatekeeper for changes to shared knowledge structures
Ensure semantic models are reusable across capabilities
Requirements
Bachelor's degree or equivalent experience
Nice to have: Contract Lifecycle Management platforms
Lead the technical architecture and engineering leadership for ServiceNow’s Context Engine, driving design, implementation, and adoption of AI-native data infrastructure.
Compensation
For positions in this location, we offer a base pay of $221,200 - $387,100, plus equity (when applicable), variable/incentive compensation and benefits.
Responsibilities
Own the technical architecture of core components across the data lake and Context Engine
Lead design and implementation of lakehouse table services and context graph ingestion
Translate product requirements into scalable, observable plans with clear failure-recovery patterns
Design how large language models and enterprise ontologies work together in the Context Engine
Drive the full arc from early release to meaningful adoption
Requirements
Advanced degree in Computer Science, AI, or a related field
Nice to have: knowledge graph or context graph experience
The role involves designing, building, and governing the enterprise context layer (AI, Ontology & Knowledge Graphs) to power next-generation AI, analytics, and decision intelligence solutions. It sits at the intersection of Data Engineering, Ontology Design, Knowledge Graphs, Semantic Technologies, and Agentic AI.
Responsibilities
Design semantic models, ontologies, and taxonomies
Define business entities, concepts, relationships, and hierarchies
Establish enterprise-wide semantic standards and reusable patterns
Create contextual representations of business processes and decision flows
Design and implement knowledge graphs
Requirements
Bachelor's degree in business, information systems or related discipline
Nice to have: Leadership and people management skills
Nice to have: Written and verbal communication skills
Graph Engineer / Ontologist to design, develop, and implement enterprise knowledge graphs and semantic data solutions in a regulated financial‑services environment.
Responsibilities
Design and develop knowledge graphs, ontologies, taxonomies, and semantic information models
Translate business, operational, financial, and regulatory requirements into formal graph and ontology specifications
Define entities, relationships, attributes, constraints, classifications, and semantic rules
Develop graph data models using RDF, OWL, SKOS, SHACL, SPARQL, property‑graph models and Cypher
Build data‑mapping and ingestion processes from relational databases, APIs, documents, and other enterprise data sources
Requirements
Relevant degree or equivalent experience in computer science, information systems, data science, mathematics, engineering, or a related field
Nice to have: Experience in banking, capital markets, financial services, risk, compliance, or regulatory data
Nice to have: Knowledge of financial‑industry standards and reference models such as FIBO, ISO 20022, LEI
Nice to have: Experience with data lineage, metadata management, master data management, data catalogues, or data governance
Nice to have: Familiarity with cloud platforms, containerisation, CI/CD, and infrastructure‑as‑code
Responsible for definition, governance and stewardship of Argus semantic assets, including ontologies, taxonomies, thesauri, glossaries, controlled vocabularies and semantic reference data.
Compensation
Competitive salary and company bonus scheme
Responsibilities
Define semantic requirements and evaluate candidate concepts for governance and modelling
Design and maintain ontologies, taxonomies, thesauri, glossaries and controlled vocabularies
Operate semantic governance processes and approval workflows
Manage the lifecycle of semantic assets from proposal through retirement
Conduct quality reviews, impact assessments and change management activities
Data ModellerNewHSBC · Sheffield, United Kingdom
Senior Semantic EngineerArgus Media · London