Graph Data Engineer – AI & Semantic Systems

Galent is seeking a highly skilled Data Engineer with expertise in knowledge graphs, semantic modeling, and AI context systems. The ideal candidate will design and implement scalable graph-based data architectures, enabling advanced analytics and LLM-driven applications through robust semantic layers and context protocols.

Responsibilities:

• Design and implement knowledge graphs and context graphs, including:
• Entity resolution and identity matching
• Relationship modeling and schema design
• Graph traversal techniques and optimization
• Develop scalable graph data architectures to support complex data relationships and queries
• Architect and implement semantic layers that:
• Translate business requirements into technical data models
• Define standardized metrics and KPIs
• Enforce governed and secure data access patterns
• Ensure consistency, usability, and performance of semantic abstractions across systems
• Build and maintain MCP (Model Context Protocol) servers to:
• Provide tool-use interfaces for LLM-driven applications
• Enable context retrieval endpoints for AI agents
• Ensure efficient, secure, and scalable delivery of contextual data to AI systems
• Design and develop semantic models through:
• Ontology engineering and taxonomy design
• Business Capability Model (BCM) mapping
• Domain-driven schema modeling
• Continuously refine ontologies to improve semantic clarity and interoperability
• Develop and manage graph databases using platforms such as:
• Amazon Neptune
• Neo4j
• Implement hybrid retrieval strategies combining:
• Graph-based queries
• Vector-based similarity search
• Optimize query performance, indexing strategies, and data ingestion pipelines
• Optimize graph query execution and data retrieval strategies to improve:
• Response times
• System scalability
• Accuracy of results
• Monitor and troubleshoot performance bottlenecks in graph-based systems
• Collaborate with cross-functional teams including data scientists, engineers, and business stakeholders to:
• Gather and analyze requirements
• Translate business needs into technical solutions
• Provide technical guidance and best practices for semantic and graph implementations
• Ensure strong data governance practices, including:
• Data quality and consistency
• Access control and security policies
• Regulatory compliance
• Maintain auditability and traceability within semantic and graph-based systems
• Stay updated with emerging technologies in:
• Graph databases
• Semantic modeling
• AI/LLM context protocols
• Proactively introduce improvements to systems, tools, and methodologies

Requirements:

• Strong experience with graph databases (Neo4j, Amazon Neptune, or similar)
• Proficiency in graph query languages (Cypher, Gremlin, SPARQL)
• Hands-on experience with knowledge graph design and ontology modeling
• Understanding of semantic web technologies and standards
• Experience building APIs or backend services (e.g., MCP servers, RESTful services)
• Familiarity with vector databases / embeddings / hybrid search
• Strong programming skills (Python, Java, or similar)
• Knowledge of data architecture, ETL/ELT pipelines, and distributed systems
• Experience with data governance and security frameworks
• Experience working with LLMs and AI agents
• Knowledge of domain-driven design (DDD) principles
• Familiarity with cloud platforms (AWS, Azure, or GCP)
• Understanding of metadata management and data cataloging tools
• Experience with real-time or streaming data architectures