The Graph Expert Services team is responsible for designing the backbone of AI readiness for our customers. Our platform combines visual, low-code modeling with graph-native context so enterprises keep relationships, lineage, and meaning intact—critical for trustworthy AI, better decisions, and faster delivery. Our customer Business and engineering teams collaborate in one workspace to design, build, and ship smarter enterprise apps quickly, turning complex connected data into clear outcomes.
We are looking for a Senior Implementation Lead to lead complex AI Fabric implementations in EMEA leveraging Knowledge Graphs, Generative AI, and the Siemens technology suite.
Key elements of the role:
Lead end-to-end implementations of RapidMiner Graph Studio and Graph Lakehouse solutions, transforming enterprise data into strategic knowledge graph platformsArchitect and deploy semantic data integration solutions using W3C standards (RDF, RDFS, OWL, SPARQL) to create enterprise-scale knowledge graphs for critical business applicationsDesign and implement ontology models that represent complex business domains, enabling semantic interoperability and advanced analytics across disparate data sourcesBuild semantic mapping frameworks to transform structured and unstructured data sources into RDF triple stores, ensuring data quality and consistencyConfigure and optimize Graphmart architectures including query templates, validation rules, search indexes, write-back mechanisms, and inference enginesIntegrate authentication and authorization frameworks (Keycloak, ABAC) with fine-grained access control policies for secure knowledge graph deploymentsImplement data virtualization strategies to provide unified semantic access layers across federated data sources without physical data movementDevelop SPARQL queries and interactive dashboards using Harris Analytics to deliver actionable insights from knowledge graph dataDeploy GenAI applications integrated with knowledge graphs to enable retrieval-augmented generation (RAG), semantic search, and AI-powered analyticsPartner with data architects and engineers to design scalable graph database architectures aligned with enterprise data governance frameworksMentor customer teams on knowledge graph best practices, semantic modeling methodologies, and Graph Studio platform capabilitiesLead workshops and enablement sessions for partners and customers, accelerating adoption and building internal competenciesTroubleshoot complex technical challenges in production environments, providing rapid resolution and continuous optimizationCollaborate with product teams to provide customer feedback, influence roadmap priorities, and contribute to platform evolutionSupport pre-sales activities by conducting technical discovery, proof-of-concept implementations, and solution architecture designChampion AI and knowledge graph adoption within customer organizations by demonstrating value through tangible business outcomes
Education:
A degree in Computer Science, Data Science, Information Systems, Software Engineering, or related technical field/Advanced certifications in semantic web technologies, knowledge graphs, or enterprise data architecture are a plus.
Experience & Skills:
8+ years of experience in enterprise software implementation, with at least 4+ years focused on AI, knowledge graphs, semantic technologies, or advanced analytics platformsProven expertise in knowledge graph platforms, semantic web standards (RDF, RDFS, OWL, SPARQL, SHACL), and graph database technologies (e.g., RDF triple stores, property graphs)Deep understanding of ontology engineering, semantic modeling, and linked data principles with hands-on experience creating production-grade ontologiesDemonstrated success leading complex, multi-stakeholder implementation projects from requirements gathering through production deploymentStrong technical skills in data integration, ETL/ELT processes, and working with diverse data sources (relational databases, NoSQL, cloud storage, APIs)Experience with GenAI technologies including large language models, vector databases, embeddings, and retrieval-augmented generation (RAG) architecturesProficiency in SPARQL for querying and manipulating RDF data, with ability to write complex federated queries and inference rulesFamiliarity with authentication/authorization frameworks such as Keycloak, OAuth2, SAML, and attribute-based access control (ABAC)Knowledge of enterprise integration patterns, API design, microservices architectures, and cloud platforms (AWS, Azure, GCP)Programming skills in Python, Java, or similar languages for scripting, automation, and extending platform capabilitiesCustomer-facing excellence: ability to build trusted advisor relationships with C-level executives, technical leaders, and business stakeholdersStrong analytical and problem-solving skills with ability to diagnose complex technical issues and design elegant solutionsExcellent communication skill - able to translate complex technical concepts into clear, business-focused narratives that drive decision-makingCollaborative mindset with proven ability to work effectively across global, cross-functional teams in matrixed organizationsGrowth-oriented approach with passion for continuous learning and staying current with emerging AI and semantic technology trendsProject management capabilities including agile methodologies, stakeholder management, risk mitigation, and delivery excellence
Other requirements:
Business-fluent English is required for effective communication in international settingsAdditional European languages (German, French, Spanish, or others) are highly valuable for regional customer engagements.
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