Graph AI Engineer

Senior Graph AI Engineer- Chicago (13+ year)

Long Term

Required Qualifications

• 5+ years of software engineering experience, with at least 3 years focused on graph databases or knowledge graph systems.
• Strong proficiency in Neo4j and Cypher query language; hands-on experience with APOC and GDS libraries.
• Demonstrated experience in ontology modeling (OWL, RDF/RDFS) and translating ontologies to labeled property graph schemas.
• Working knowledge of GDS graph algorithms - community detection, centrality, similarity, and path finding.
• Experience building LLM-powered applications, including agentic systems, RAG pipelines, and tool-calling architectures.
• Proficient in React JS for building interactive web applications and chatbot interfaces.
• Strong backend skills in Python or Java/Node.js for building APIs and data pipelines.
• Familiarity with vector databases (e.g., Pinecone, Weaviate, Qdrant) for hybrid graph+vector retrieval.

Preferred Qualifications

• Neo4j Certified Professional or equivalent graph database certification.
• Experience with LLM frameworks such as LangChain, LlamaIndex, or AutoGen.
• Familiarity with ontology editors such as Prot g and SPARQL query language.
• Knowledge of graph-native ML using PyG (PyTorch Geometric) or DGL.
• Experience in cloud environments (AWS, Azure, GCP) deploying Neo4j AuraDB or self-managed clusters.
• Understanding of enterprise data governance, data lineage, and metadata management.

What We Offer

• Opportunity to work at the cutting edge of Graph AI and Agentic systems.
• Collaborative, innovation-driven team culture with continuous learning support.
• Competitive compensation, benefits, and flexible working arrangements.
• Access to cloud credits, research publications, and AI conference sponsorships.
• Direct impact on enterprise knowledge systems used by thousands of users.