Graph Engineer
Skills
- Experience with graph databases (Stardog, Neo4j, AWS Neptune, or similar).
- Familiarity with RDF/OWL or Property Graph modeling.
- Proficiency writing and optimizing SPARQL, Cypher, or Gremlin queries.
- Scripting for ingestion/automation using Python or JavaScript.
- Experience building ETL/data transformation pipelines and working with APIs.
- Exposure to cloud platforms (AWS, Azure, or GCP).
- Basic knowledge of NLP, RAG, or AI retrieval concepts.
Responsibilities
- Design and implement knowledge graph schemas, ontologies, and entity/relationship models to support GenAI and agentic applications.
- Ingest and hydrate graphs from structured and unstructured enterprise and demo data sources using ETL pipelines.
- Develop and optimize SPARQL, Cypher, or Gremlin queries for analytics, AI retrieval, and application integration.
- Collaborate with developers and data scientists to enable semantics-driven features and knowledge-augmented generation (RAG).
- Integrate graph data with front-end agentic components and support application workflows.
- Perform performance tuning, data validation, and security/compliance checks for graph systems.
- Document ontologies, data models, graph schemas, and evolution processes.
Education
- Bachelor's degree in Computer Science, Data Science, Information Systems, or related field, or equivalent experience.
Benefits
- Medical, dental, and vision insurance
- 401(k) plan
- Tuition reimbursement and professional development
- Entrepreneurial, collaborative culture with growth and promotion opportunities
- Work culture focused on innovation and inclusion
Average salary estimate
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