Principal Engineer, Semantic Platforms and Graph Intelligence - 220772
Teradata
Our companyAt Teradata, we believe that people thrive when empowered with better information. Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI.What You’ll DoWe are seeking a world-class Principal Knowledge Graph Engineer to lead the architecture, development, and evolution of next-generation knowledge graph platforms that power AI, reasoning, discovery, and autonomous decision-making at enterprise scale for Teradata Context Engine.This role is intended for a recognized technical leader who has built and operated very large-scale knowledge graphs comprising billions of entities, relationships, events, documents, and embeddings derived from both structured and unstructured data. You will own, and drive innovation at the intersection of graph technologies, semantic modeling, information retrieval, machine learning, agents, and generative AI for Teradata Context Engine, our Autonomous Knowledge Platform. Context Engine is a platform that converts enterprise data estates into governed, agent-ready knowledge. Built for organizations where AI reliability and auditability are non-negotiable, Context Engine enables companies to deploy AI workflows on the data they already own — without rebuilding their infrastructure, without retraining their models, and without waiting for generic AI synthesis to learn the business terminology that took their analysts years to master.Technical LeadershipDefine and execute the long-term vision for enterprise knowledge graph architecture and graph-enabled AI systems.Lead the design of highly scalable graph platforms supporting billions of nodes and edges across multiple data domains.Establish standards, frameworks, and best practices for graph modeling, ontology design, semantic interoperability, and graph lifecycle management.Serve as the company's senior technical authority on graph technologies, semantic systems, and knowledge representation.Knowledge Graph ArchitectureDesign and implement large-scale knowledge graphs that integrate:Structured enterprise dataSemi-structured dataDocuments and content repositoriesEvent streamsAPIs and external data sourcesEmbedding and vector representationsLLM-generated knowledge artifactsDevelop scalable entity resolution, identity graph, and record-linkage frameworks.Build semantic layers that unify business concepts across disparate systems.AI, Retrieval & ReasoningDesign hybrid retrieval architectures combining:Knowledge graphsVector databasesFull-text searchSemantic retrievalAgentic workflowsEnable GraphRAG and graph-enhanced AI experiences.Develop graph-based reasoning systems that support explainable AI and autonomous decision-making.Apply graph algorithms, network analysis, and graph machine learning to generate insights and predictions.Engineering & Platform DevelopmentBuild distributed graph ingestion and processing pipelines for large-scale enterprise environments.Optimize graph performance, storage, indexing, partitioning, caching, and query execution.Implement graph observability, quality assurance, lineage, governance, and monitoring capabilities.Contribute production-grade code and lead the development of reusable graph services and platforms.Industry LeadershipStay at the forefront of advancements in:Knowledge graphsSemantic technologiesGraph databasesGraph machine learningRetrieval systemsAI agentsLarge and small language modelsPublish technical papers, patents, blogs, conference talks, and thought leadership where appropriate.Mentor senior engineers and influence architecture across the organization.A plus would be in-depth knowledge in at least one vertical, such as Healthcare, Finance, etc.Who You’ll Work WithYou will work hands-on across the full lifecycle of graph systems, from ontology engineering and graph construction to retrieval, reasoning, embeddings, graph machine learning, and AI-powered applications. This is not a management role. We are looking for a builder, architect, and technical thought leader who can design systems, write code, solve hard problems, and influence strategy.What Makes You a Qualified CandidateExperience12+ years of software engineering experience.8+ years designing and implementing enterprise-scale graph systems.Proven experience building and operating knowledge graphs with hundreds of millions to billions of nodes and relationships.Demonstrated success integrating structured, semi-structured, and unstructured data into production graph platforms.Experience leading architecture for mission-critical data or AI platforms.Deep Knowledge of Graph TechnologiesExpert-level understanding of:Property graphsRDF, RDFS, OWLKnowledge representation and reasoningOntology design and semantic modelingTaxonomy developmentEntity resolution and identity graphsGraph query languages:CypherSPARQLGremlinGraphQLGraph PlatformsStrong experience with several of:JanusGraphNeo4jAmazon NeptuneTigerGraphMemgraphArangoDBStardogOntotext GraphDBVirtuosoAI and Machine LearningHands-on experience with:GraphRAG architecturesRetrieval-augmented generationGraph embeddingsKnowledge-enhanced LLM systemsVector databasesGraph neural networksLink predictionNode classificationRecommendation and ranking systemsLarge-Scale Data EngineeringExpertise in:Distributed systemsStreaming architecturesSparkKafkaData pipelinesData governanceData qualityMetadata managementCloud-native architecturesSoftware EngineeringStrong coding ability in:PythonJavaScalaGoC#Experience with:API designDistributed computingContainerizationKubernetesCI/CDCloud-native developmentWhat You’ll BringPhD or MS in Computer Science, Information Science, Knowledge Representation, Artificial Intelligence, Machine Learning, or related disciplines.Contributions to widely adopted graph technologies or open-source projects.Published research in knowledge graphs, semantic technologies, graph machine learning, information retrieval, or AI.Experience building enterprise GraphRAG platforms at production scale.Experience developing graph-powered autonomous agents and AI systems.Experience deploying semantic systems in air-gapped, on-prem and regulated environments.Experience developing agent harnesses on open-source (e.g., strands, LangChain), Azure, AWS and GCP platforms.Recognized industry expert, conference speaker, or technical thought leader.Characteristics of an exceptional candidateThe ideal candidate has personally:Built knowledge graphs containing billions of entities and relationships.Designed ontologies spanning multiple enterprise domains.Solved large-scale entity resolution and identity graph challenges.Integrated graph, vector, and search technologies into unified retrieval platforms.Leveraged knowledge graphs to improve AI reasoning, explainability, and decision-making.Led architecture decisions that influenced organizations, products, and platforms at industry scale.Remained deeply hands-on despite operating at a principal or distinguished engineer level.Success metricsWithin the first 12 months, you will:Establish a scalable enterprise knowledge graph architecture.Accelerate GraphRAG and AI capabilities through graph-enhanced retrieval and reasoning.Improve knowledge discovery, relationship analysis, and semantic interoperability across the enterprise.Enable graph-powered applications that drive measurable business and operational outcomes.Raise the technical bar for graph engineering, semantic technologies, and AI platform architecture across the organization.Why We Think You'll Love Teradata We prioritize a people-first culture because we know our people are at the very heart of our success. We embrace a flexible work model because we trust our people to make decisions about how, when, and where they work. We focus on well-being because we care about our people and their ability to thrive both personally and professionally. We are committed to actively working to foster an inclusive environment that celebrates people for all of who they are#LI-CP2 Teradata is proud to be an equal opportunity employer. We do not discriminate based upon race, color, ancestry, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related conditions), national origin, sexual orientation, age, citizenship, marital status, disability, medical condition, genetic information, gender identity or expression, military and veteran status, or any other legally protected status. We welcome and encourage individuals from all backgrounds to apply and join our team, bringing their unique perspectives and experiences to help us innovate and grow. If you require accommodations during the interview process, please let your recruiter know and we will work with you to meet your needs.
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