Senior Graph Engineer (Python)

Evolver • Palo Alto, CA

1d • Hybrid

About The Position

Join an AI startup focused on transforming professional services through Generative AI and deep domain expertise. Its agent-driven solutions automate complex workflows and engage humans when needed to improve efficiency and accuracy. The Senior Graph Engineer will join the Data & Knowledge team to design, develop, and deploy graph-based systems that connect structured and unstructured data, support complex queries, and improve AI retrieval and reasoning. The role works closely with AI engineers and domain experts to turn enterprise information into reliable, actionable knowledge.

Requirements

• At least 6 years of professional software engineering experience, with strong Python expertise.
• At least 2 years of hands-on experience developing graph-based applications, knowledge graphs, or graph data platforms.
• Advanced proficiency in Python and libraries such as 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, and 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 explaining 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.
• Comfort navigating ambiguity and evolving priorities in a fast-paced startup.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Nice To Haves

• Experience using knowledge graphs in AI or agentic applications to support graph or hybrid Graph-RAG retrieval.
• Familiarity with GraphRAG, hybrid graph and vector retrieval, or agent tools.

Responsibilities

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

Benefits

• Competitive compensation tailored to experience and skill set.
• Flexible work arrangements with a hybrid working model.
• Opportunities for professional development and technical leadership.
• Opportunity to build technologies connecting enterprise knowledge and powering AI applications.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior