Lead AI Engineer (Knowledge Graph / Ontology & Agentic AI)
Job Description – Lead AI Engineer (Knowledge Graph / Ontology & Agentic AI)Location: Dallas, TXRole SummarySeeking a Lead AI Engineer with strong expertise in Knowledge Graph (KG), Ontology modeling, and Generative AI (LLMs, Agentic AI) to design and scale a Customer Knowledge Graph platform using Neo4j and App Orchid. The role will lead AI product/platform development, enabling relationship intelligence, Customer 360 insights, and AI-driven decisioning.Key ResponsibilitiesKnowledge Graph & Ontology (Neo4j / App Orchid)Design and implement ontology models and semantic frameworksBuild and scale Customer Knowledge Graph using Neo4j and App OrchidDevelop entity resolution, relationship mapping, and enrichment pipelinesWrite and optimize graph queries (Cypher) for analytics and insightsManage performance, scalability, and governance of KG platformAI & Agentic AI DevelopmentArchitect and implement Agentic AI and multi-agent systemsLeverage LLMs and RAG with Knowledge Graph for contextual intelligenceEnable capabilities such as:Customer 360 insightsRelationship discovery & scoringNatural language querying (Graph/SQL agents)Drive end-to-end AI lifecycle (design → deploy → optimize)Data Engineering & IntegrationBuild scalable pipelines to integrate enterprise data into KGImplement customer identity resolution and data quality frameworksDesign APIs for application and AI model integrationLeadership & Platform OwnershipLead AI platform architecture and roadmapMentor engineering teams and enforce best practicesDrive AI-first SDLC adoption and enterprise scalingCollaborate with business, data science, and engineering stakeholdersRequired SkillsKnowledge Graph & Ontology: RDF, OWL, semantic modelingGraph Platforms: Strong hands-on with Neo4j and App OrchidGraph Querying: Cypher (mandatory)AI/GenAI: LLMs, RAG, Agentic AI (CrewAI/LangGraph)Programming: Python (AI + data engineering)Data Engineering: Spark, Kafka, Airflow (or equivalent)Cloud: AWS / AzureMLOps/DevOps: CI/CD, scalable system designPreferred SkillsCustomer 360 / Customer Data PlatformsGraph analytics (community detection, centrality)Graph visualization toolsExposure to GNNsDocker / KubernetesLeadership ExpectationsOwn AI product/platform delivery end-to-endDefine technical roadmap and architecture strategyDrive enterprise AI adoption with business impact (revenue, engagement)