Summary: Own the technical vision and roadmap for SAP’s Industry Knowledge Graph, providing leadership to a multidisciplinary team of engineers and scientists. Define ontologies, SHACL constraints, and KG construction pipelines while integrating Knowledge Graphs with Large Language Models to enable scalable AI on enterprise...

We help the world run better
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.

What you'll build

At SAP Business AI, we are exploring the next frontier of AI on structured business data like graphs, tables and more. Foundation Models on structured data, like SAP-RPT-1, have ushered in the GenAI era for business relevant scenarios. Now, we are pushing further. We want to enable companies across all industries to collaboratively train foundation models and build knowledge graphs.

As Knowledge Graph Tech Lead (f/m/d), you will own the technical vision and roadmap for SAP’s Industry Knowledge Graph (IKG) – a unified, semantically rich representation of business entities, processes, and relationships across SAP applications and customer industries. You provide technical leadership for a team of knowledge engineers, data engineers, and AI scientists, leading through expertise, mentorship, and influence rather than direct people-management responsibility, enabling the modeling of industry data into a production-grade RDF Knowledge Graph for open-source delivery, shaping the IKG into a platform that other workstreams (Multi-Modal Industry Foundation Models and Data Platform) and SAP product teams build on, and pushing the frontier of how Knowledge Graphs and Large Language Models combine to enable the creation of new knowledge at scale.

You move easily between deep technical work – ontologies, SHACL shapes, SPARQL, KG construction pipelines – and shaping the broader IKG architecture and roadmap that several teams across the initiative will execute against.

This is the ideal role for a highly technically focused, ambitious individual with exceptional depth in Knowledge Graphs and a proven track record of shaping and leading large-scale engineering and research efforts. This is a rare opportunity to define the data backbone for one of the very few foundation-model programs of European origin and help shape the future of AI on enterprise data.

The Role

Define and own the architectural and research roadmap for the Industry Knowledge Graph – ontology design, SHACL constraints, KG construction at scale, and the path from prototypes to production and delivery as open-source project.
Provide technical and thought leadership to a multidisciplinary team of knowledge engineers, data engineers, and AI scientists; set the technical bar, drive hypotheses and experiments, and steer execution from concept through production (without direct people-management responsibility)
Redefine what end-to-end KG construction means in the age of Agentic AI – from initial modeling to mapping diverse sources all the way to researching joint representations of latent and explicit knowledge.
Shape the IKG to become part of the OP4I platform with clear interfaces that the MMIFM and SAP product teams build on, with documentation, blueprints and onboarding for downstream consumers
Push the frontier of Knowledge Graph and Foundation Model integration through agent grounding, agentic knowledge engineering, and the use of the IKG to train better foundation models, partnering with the MMIFM team and product stakeholders.

What you bring

PhD or Master’s degree in Computer Science, Artificial Intelligence, Knowledge Representation, or related disciplines
Typically 12+ years of relevant industry and/or research experience in Knowledge Graphs, data engineering, AI, or related fields, including experience driving complex initiatives from concept to production
A strong vision of how KG construction should be done in the age of Agentic AI, demonstrated e.g. by recent academic publications in top tier conferences
Deep, hands-on expertise in the RDF Knowledge Graph stack (RDF, RDFS, OWL, SHACL, SPARQL) with a track record of taking enterprise Knowledge Graphs from concept to production at scale
Demonstrated experience leading the technical direction of a KG / data engineering effort – ontology design, KG construction pipelines, and integrating the graph into a platform that other teams build on
Hands-on experience integrating Knowledge Graphs with LLMs – e.g. graph RAG, KG embeddings, KG-grounded agents, hallucination mitigation
Knowledge of SAP business data and applications – data models, business objects, extraction interfaces – is a strong plus; broader familiarity with enterprise data (ERP, CRM) is welcome
Familiarity with the triple-store ecosystem (commercial and open-source: GraphDB, Stardog, Virtuoso, Apache Jena, Blazegraph, Neptune, etc.), SPARQL query optimization, and KG operations at scale is a plus
Proven technical leadership and outstanding communication skills for technical and non-technical audiences
You can defend an ontology decision in a deep technical review just as effectively as you can explain the value of a Knowledge Graph to business stakeholders and executives
Excellent written and verbal English communication skills at business level are required; additional languages are a plus

Where you belong

SAP's AI organization is dedicated to seamlessly infusing AI into all enterprise applications, enabling customers, partners, and developers to enhance business processes and generate remarkable business value. Join our international AI team where innovation thrives, opportunities for personal development abound, and exceptional colleagues collaborate globally.

#SAPBusinessAICareers

Bring out your best

SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.

We win with inclusion
SAP’s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.

SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com.

For SAP employees: Only permanent roles are eligible for the [SAP Employee Referral Program](https://one.int.sap/me@sap/jobs_and_hiring/employee_referral/region/0000/lang/en), according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.

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Knowledge Graph Tech Lead (m/f/d)

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