Senior Implementation Lead (m/f/d)
Mendix
Posted on Dec 25, 2025
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 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
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 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, NoSQL, 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
Other requirements:
- Business-fluent English is required for effective communication in international settings
- Additional European languages (German, French, Spanish, or others) are highly valuable for regional customer engagements.
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