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- Tasks: Lead AI implementations and design knowledge graph platforms for smarter enterprise apps.
- Company: Join a forward-thinking tech company focused on AI and data innovation.
- Benefits: Enjoy flexible working, wellness perks, and generous health coverage.
- Why this job: Make a real impact in AI and knowledge graphs while collaborating with top talent.
- Qualifications: 8+ years in software implementation with expertise in AI and knowledge graphs.
- Other info: Dynamic role with opportunities for growth and continuous learning.
The predicted salary is between 60000 - 84000 £ per year.
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 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.
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 skills - 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 regional customer engagements.
Benefits:We provide generous benefits that support our employees’ wellbeing, no matter where they’re located. We also offer region-specific benefits, like fully-stocked office kitchens, commuter perks, and more!
- Flexible, hybrid working
- Flexible paid time off
- Medical, Dental, and Vision Coverage
- 401k matching
- Wellness benefits
- Siemens employee discounts
- Bravely career coaching
Benefits may vary depending on location.
Senior Graph Implementation Lead, Expert Services (m/f/d) in London employer: Mendix
Contact Detail:
Mendix Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Graph Implementation Lead, Expert Services (m/f/d) in London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or a personal project that highlights your expertise in knowledge graphs and AI. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common questions related to graph technologies and AI. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Senior Graph Implementation Lead, Expert Services (m/f/d) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Graph Implementation Lead role. Highlight your expertise in knowledge graphs, AI technologies, and any relevant projects you've led.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about this role and how your background makes you a perfect fit. Share specific examples of your past successes in implementing complex solutions.
Showcase Your Technical Skills: Don’t forget to mention your proficiency in semantic web standards and programming languages. We want to see your hands-on experience with tools like SPARQL and your understanding of data integration processes.
Apply Through Our Website: We encourage you to submit your application through our website for the best chance of being noticed. It’s the easiest way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Mendix
✨Know Your Graphs
Make sure you brush up on your knowledge of graph databases and semantic technologies. Be ready to discuss your experience with RDF, SPARQL, and ontology engineering. The more specific examples you can provide about your past projects, the better!
✨Showcase Your Leadership Skills
As a Senior Implementation Lead, you'll need to demonstrate your ability to lead complex projects. Prepare to share stories about how you've successfully managed multi-stakeholder implementations and mentored teams. Highlight your project management skills and any agile methodologies you've used.
✨Communicate Clearly
You’ll be working with C-level executives and technical leaders, so practice translating complex technical concepts into clear, business-focused narratives. Think about how you can convey the value of knowledge graphs and AI in a way that resonates with non-technical stakeholders.
✨Prepare for Technical Challenges
Expect to face some technical questions or scenarios during the interview. Brush up on troubleshooting techniques and be ready to discuss how you've resolved complex issues in production environments. Show them your analytical and problem-solving skills in action!
