Senior Graph Engineer (Python)

Evolver is an AI startup building agent-driven solutions for professional services. The Senior Graph Engineer designs, develops, and deploys graph-based systems that connect enterprise data, support complex queries, and improve AI retrieval and reasoning.

Responsibilities

• **Graph Architecture and Modeling:** Design and build scalable knowledge graphs, defining schemas, ontologies, entities, and relationships that reflect complex business domains
• **Data Integration:** Build pipelines that extract, normalize, and connect data from documents, databases, and external systems, with support for incremental updates
• **Entity Resolution and Data Quality:** Implement entity matching, deduplication, relationship validation, and provenance tracking to maintain trustworthy graph data
• **Graph Retrieval and AI Integration:** Develop graph-based retrieval capabilities and integrate them with vector search, RAG systems, and AI agents
• **Performance and Reliability:** Optimize graph queries, indexing, and storage; implement testing, monitoring, access controls, and recovery practices
• **Python Development:** Develop production-grade services, APIs, and pipelines for graph ingestion, querying, and integration with enterprise applications

Skills

• 6+ years of professional software engineering experience, with strong expertise in Python
• 2+ years of hands-on experience developing graph-based applications, knowledge graphs, or graph data platforms
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• Advanced proficiency in Python and libraries like NetworkX, Pandas, NumPy, or similar
• Strong understanding of graph data modeling, graph traversal, indexing, and query optimization
• Hands-on experience with a graph database such as Neo4j, Amazon Neptune, or Azure Cosmos DB for Apache Gremlin
• Proficiency in a graph query language such as Cypher, Gremlin, or SPARQL, with an understanding of property graph or RDF models
• Experience building data ingestion and transformation pipelines across structured and unstructured sources
• Familiarity with entity resolution, ontology design, data lineage, and graph data quality practices
• Excellent communication skills, including the ability to explain graph concepts and technical tradeoffs to nontechnical stakeholders
• Strong analytical and problem-solving skills, with attention to data quality and system reliability
• Ability to own projects from design through deployment and collaborate across disciplines
• Comfortable navigating ambiguity and evolving priorities in a fast-paced startup
• Ideally, experience using knowledge graphs in AI/agentic applications to support graph or hybrid Graph-RAG retrieval
• Familiarity with knowledge graphs in AI applications, including GraphRAG, hybrid graph and vector retrieval, or agent tools, is a plus

Benefits

• Hybrid working model for work-life balance.
• Opportunities for professional development and technical leadership.

Company Overview

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