Ontology & Knowledge Graph Engineer
Lambda256 Co., Ltd. is a Seoul-based blockchain technology company and Dunamu subsidiary operating enterprise Web3 infrastructure.
Maintainer signals as of 9/25/2026
Funding history
About Lambda256 Co., Ltd.
Lambda256 originated as Dunamu's blockchain research division and became an independent corporation in March 2019. Its current products include Nodit, an institutional-grade multichain node and blockchain-data infrastructure platform; CLAIR, an ontology-based blockchain intelligence and FRAML engine; and SCOPE, an institutional stablecoin issuance, payments, settlement, wallet, and compliance platform. Lambda256 also operates Nodit services including Datashare, Datasquare, validator operations, Web3 Data APIs, webhooks, MCP, and x402-based agentic payments.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will analyze customer and internal domain problems and translate them into concept models and ontologies. You will design and build ontology-based knowledge graph solutions for analysis, exploration, reasoning, and AI use cases. You will support proofs of concept and early implementations through modelling, solution design, data validation, mapping, loading, and consistency checks.
Requirements
- Understand and structure complex customer problems
- Rapidly learn new domains and organize them into concept models
- Apply ontologies and knowledge graphs to real business problems
- Participate in problem definition, modelling, solution design, and proof-of-concept leadership
- Assess implementation feasibility while consulting and modelling
Responsibilities
- Analyze customer and internal domain problems and participate in consulting
- Design domain concept models and ontologies
- Identify ontology-based knowledge graph use cases and build pipelines for analysis, exploration, reasoning, and solution implementation
- Perform modelling, solution design, and data validation for proofs of concept and early implementations
- Map, load, validate, and develop models using real data in collaboration with others
Hiring Process
Application review → coding test → first role interview → second culture-fit interview → compensation discussion → final offer
