Applied AI Engineer, Knowledge Graph

Applied AI Engineer, Knowledge Graph OpenGov is the leader in AI and ERP solutions for local and state governments in the U.S. More than 2,000 cities, counties, state agencies, school districts, and special districts rely on the OpenGov Public Service Platform to operate efficiently, adapt to change, and strengthen the public trust. Category-leading products include enterprise asset management, procurement and contract management, accounting and budgeting, billing and revenue management, permitting and licensing, and transparency and open data. These solutions come together in the OpenGov ERP, allowing public sector organizations to focus on priorities and deliver maximum ROI with every dollar and decision in sync. Learn about OpenGov’s mission to power more effective and accountable government and the vision of high-performance government for every community at OpenGov.com http://OpenGov.com. JOB SUMMARY OpenGov is seeking an Applied AI Engineer, Knowledge Graph to design and evolve the semantic data layer that gives our AI systems a structured, relationship-aware understanding of government data. You will be among the first members of our Pune AI engineering team, working at the intersection of data modeling, semantic engineering, and applied AI. This role centers on graph database engineering and semantic data modeling. You think in relationships and meaning—not just rows and columns—and you have the technical depth to translate complex business domains into well-structured, maintainable graph schemas. You may not have deep AI-specific experience coming in, and that is by design: what this role requires most is strong graph fundamentals, business semantic understanding, and the communication skills to bridge technical and non-technical stakeholders with precision. Communication is a core technical competency for this role, not a soft skill. You will work across engineers, analysts, product managers, and business domain experts. Your ability to translate between them—accurately and clearly—is what makes the knowledge graph actually useful. Candidates who prefer to model schemas in a task-oriented way, or in isolation, will not thrive here. CORE RESPONSIBILITIES - Design, build, and maintain the knowledge graph structures that represent OpenGov’s enterprise data domains, internal (employee) and external (customer) entities, relationships, and product events across areas such as budgeting, procurement, permitting, and finance. - Model semantic relationships within and across workflows to reflect real-world business logic, not just technical convenience, and keep those models accurate as business requirements evolve. - Collaborate closely with OpenGov’s Data Engineering and R&D/Product Engineering teams to align graph schemas with production data models, data lineage, and evolving ontologies. - Work directly with product owners, domain experts, and non-technical stakeholders to understand business semantics and translate them into accurate, queryable graph structures. - Document schema decisions, ontology changes, and data lineage in language accessible to both engineers and business stakeholders as shared organizational knowledge, not just internal notes. - Contribute to the integration of the knowledge graph with AI systems: enabling graph-grounded retrieval, entity resolution, and structured context injection for LLM workflows. - Identify and resolve inconsistencies between the graph layer and upstream data sources before they propagate into AI outputs or user-facing features. - Partner with senior AI Engineer and AI Architect resources to ensure the knowledge graph is queryable, performant, and integrated into AI pipelines in a maintainable way. REQUIRED EXPERIENCE - Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field. - 3–6 years of hands-on experience with graph databases (Neo4j, Amazon Neptune, TigerGraph, ArangoDB, or similar) in a production or near-production context. ... (truncated, view full listing at source)