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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Software Developer - **Company:** OCTAVE LLC - **Location:** Houston, TX, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Encodings, Information Engineering, Query Languages, Graph Database, JSON, Python (Programming Language), Neo4j, Octave, Open Data Protocol, Parsing, Software Engineering, SPARQL, Management of Software Versions, Openapi, Large Language Models, Prompt Engineering, Spring-boot, Backend, Microsoft Fabric, Graphql - **Published:** September 27, 2026 - **Apply:** https://www.dice.com/job-detail/0aa8dda0-5311-4e7f-b8c4-da5ddc5d905c ## About the Role * 5+ years in data or knowledge engineering, with specific experience designing and building graph data models for production systems * Deep familiarity with labeled property graph (LPG) data models and graph databases (Neo4j, Amazon Neptune, or comparable) * Experience with graph query languages - Cypher, SPARQL, or GraphQL over graph data * Strong understanding of ontology design principles - entity modeling, relationship semantics, property typing, and ontology versioning * Hands-on experience with OData and/or OpenAPI schema parsing and transformation * Proficiency in Java or Python - the ontology tool backend is a Spring Boot Java application * Experience with LLM-assisted data engineering: prompt engineering for structured JSON output, schema synthesis, and mapping validation * Strong data modeling instincts - understanding when to normalize vs. denormalize, how to handle temporal data, and how to design for queryability * Ability to work with domain experts to translate institutional knowledge into formal schema constructs Preferred: * Experience with industrial ontology standards (ISO 15926, OSDU, IFC, ISA-95) * Background in capital project delivery, EPC, or industrial asset management domains * Familiarity with Microsoft Fabric Delta tables as a graph construction source * Experience with knowledge graph contextualization and entity matching at scale ## Description The Graph Engineer owns the Octave platform's knowledge graph - the canonical, cross-product representation of industrial intelligence that powers every agent, model, and application built on the platform. This role sits at the intersection of knowledge engineering, graph data modeling, and software engineering. The Graph Engineer is responsible for designing the ontology that makes cross-domain reasoning possible, building and operating the graph construction pipeline, and ensuring the graph remains trustworthy, current, and queryable at the quality level the platform's intelligence depends on. * Own the Octave canonical ontology - the labeled property graph (LPG) schema that unifies entities across Design, Build, Operate, and Protect product domains into a single coherent knowledge model * Lead the ongoing development of the ontology authoring tool (the Platform Studio Data Engineering Tool), including schema parsing, LLM-assisted canonical synthesis, and Fabric notebook generation * Design and implement the entity resolution layer - the mechanism that reconciles cross-product identities (e.g. Pump P-401 in Forte 3D = P-401 in Sequence = asset #4017734 in Attune) with deterministic, stable cross-product identifiers * Own provenance and lineage at the graph level - ensuring every node and edge carries source attribution, freshness metadata, and conflict resolution records * Collaborate with domain experts across product teams to extract institutional knowledge and encode it into the ontology's domain taxonomy, JTBD libraries, and relationship semantics * Design the query surface exposed to Aria agents - graph traversal patterns, MCP tool schemas for graph access, and the semantic contract agents rely on * Drive ontology versioning discipline: schema evolution strategy, deprecation policy, and compatibility guarantees for downstream consumers * Contribute to the knowledge engineering methodology - the process for eliciting tacit domain expertise from capital project practitioners and encoding it into the graph ## Related Videos - [New AI-Centric SDLC: Rethinking Software Development with Knowledge Graphs](https://www.wearedevelopers.com/videos/1417-new-ai-centric-sdlc-rethinking-software-development-with-knowledge-graphs) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [Graphs and RAGs Everywhere... But What Are They? - Andreas Kollegger - Neo4j](https://www.wearedevelopers.com/videos/1311-graphs-and-rags-everywhere-but-what-are-they-andreas-kollegger-neo4j) - [Cyber Sleuth: Finding Hidden Connections in Cyber Data](https://www.wearedevelopers.com/videos/893-cyber-sleuth-finding-hidden-connections-in-cyber-data) - [Your organization as a Graph](https://www.wearedevelopers.com/videos/2051-your-organization-as-a-graph) ## Related Articles - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [The Best X (Twitter) Accounts for Developers](https://www.wearedevelopers.com/magazine/294-the-best-x-twitter-accounts-for-developers) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)