Senior Implementation Lead; m​/f​/d

Key elements of the role:

• Lead end-to-end implementations of Rapid Miner Graph Studio and Graph Lakehouse solutions, transforming enterprise data into strategic knowledge graph platforms

• Architect and deploy semantic data integration solutions using W3C standards (RDF, RDFS, OWL, SPARQL) to create enterprise-scale knowledge graphs for critical business applications

• Design and implement ontology models that represent complex business domains, enabling semantic interoperability and advanced analytics across disparate data sources

• Build semantic mapping frameworks to transform structured and unstructured data sources into RDF triple stores, ensuring data quality and consistency

• Configure and optimize Graphmart architectures including query templates, validation rules, search indexes, write-back mechanisms, and inference engines

• Integrate authentication and authorization frameworks (Keycloak, ABAC) with fine-grained access control policies for secure knowledge graph deployments

• Implement data virtualization strategies to provide unified semantic access layers across federated data sources without physical data movement

• Develop SPARQL queries and interactive dashboards using Harris Analytics to deliver actionable insights from knowledge graph data

• Deploy GenAI applications integrated with knowledge graphs to enable retrieval-augmented generation (RAG), semantic search, and AI-powered analytics

• Partner with data architects and engineers to design scalable graph database architectures aligned with enterprise data governance frameworks

• Mentor customer teams on knowledge graph best practices, semantic modeling methodologies, and Graph Studio platform capabilities

• Lead workshops and enablement sessions for partners and customers, accelerating adoption and building internal competencies

• Troubleshoot complex technical challenges in production environments, providing rapid resolution and continuous optimization

• Collaborate with product teams to provide customer feedback, influence roadmap priorities, and contribute to platform evolution

• Support pre-sales activities by conducting technical discovery, proof-of-concept implementations, and solution architecture design

• Champion AI and knowledge graph adoption within customer organizations by demonstrating value through tangible business outcomes

• 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.

• 8+ years of experience in enterprise software implementation, with at least 4+ years focused on AI, knowledge graphs, semantic technologies, or advanced analytics platforms

• Proven 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 ontologies

• Demonstrated success leading complex, multi-stakeholder implementation projects from requirements gathering through production deployment

• Strong technical skills in data integration, ETL/ELT processes, and working with diverse data sources (relational databases, No
  
  SQL, cloud storage, APIs)

• Experience with GenAI technologies including large language models, vector databases, embeddings, and retrieval-augmented generation (RAG) architectures

• Proficiency in SPARQL for querying and manipulating RDF data, with ability to write complex federated queries and inference rules

• Familiarity 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 capabilities

• Customer-facing excellence: ability to build trusted advisor relationships with C-level executives, technical leaders, and business stakeholders

• Strong analytical and problem-solving skills with ability to diagnose complex technical issues and design elegant solutions

• Excellent communication skill - able to translate complex technical concepts into clear, business-focused narratives that drive decision-making

• Collaborative mindset with proven ability to work effectively across global, cross-functional teams in matrixed organizations

• Growth-oriented approach with passion for continuous learning and staying current with emerging AI and semantic technology trends

• Project management capabilities including agile methodologies, stakeholder management, risk mitigation, and delivery excellence

• Business-fluent English is required for effective communication in international settings

• Additional European languages (German, French, Spanish, or others) are highly valuable for…