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.
The context engine that makes AI enterprise ready.
Anyone can build an AI agent. What makes SAP's agents different is accuracy grounded in the richest enterprise data and process context in the world. As a Data and Applied Scientist at SAP, you'll help build the context engine grounded in SAP's Business Ontology: the semantic infrastructure that transforms raw business data into the knowledge layer powering SAP's AI agents and assistants.
This is an early-career role for engineers and scientists who are sharp, curious, and ready to do real work on hard problems from day one.
What you'll build
You'll contribute to the semantic and contextual foundation of SAP's AI. While generic AI agents operate on surface-level patterns, SAP agents are accurate because they understand the real semantics of enterprise business master data, process flows, and domain relationships. You'll work alongside senior scientists and engineers to build and scale the layer that makes that possible.
Support the design and maintenance of enterprise ontologies and semantic models that give AI agents accurate, grounded understanding of SAP and connected business landscapes — learning how data from SAP, Salesforce, Workday, ServiceNow, MES/IoT systems, and external providers gets harmonized into unified semantic layers.
Contribute to AI capabilities including RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding that make SAP's agents accurate and reliable in production.
Develop and iterate on AI solutions — including generative AI and LLM-based approaches — using enterprise business data, knowledge graphs, business process intelligence, and structured and unstructured data assets.
25 (UK) 30 (Germany) 21 (India) days annual leave + bank holidays
Accrued annual leave – 1 day/year up to 30 days (UK)
Open to job sharing
Sabbaticals
Adoption leave – Up to 52 weeks (UK)
Open to part time work for some roles
Returnship
Equity packages
Shared parental leave
Enhanced maternity leave
Fertility benefits
Pregnancy support
On-site childcare
Share options
Electric Car Salary Sacrifice
Gym membership
Dental coverage
Health insurance
Private GP service
Mental health platform access
Life assurance
Life insurance
Enhanced pension match/contribution
Enhanced paternity leave
Travel insurance
Cycle to work scheme
On-site gym
Bike parking
Enhanced sick pay
Emergency leave
Enhanced sick days
Company car
Open to part-time employees
Work from anywhere scheme
Childcare credits
Fertility treatment leave
Pregnancy loss leave
Carer’s leave
Nursery salary sacrifice scheme
Family health insurance
Women’s health leave
Annual bonus
401K
Referral bonus
Joining bonus
Employee discounts
Loyalty programme
Non-contributory pension
Personal development days
Personal development budgets
L&D budget
Language lessons
Learning license
Study support
Studying sabbaticals
Lunch and learns
In house training
Hackathons
Professional subscriptions
Further education support
Awards & Accreditations
Top 10 - Best Workplace Benefits
Flexa awards 2026
Learn SAP's deep data and process context — data models, metadata structures, and business process semantics across Order-to-Cash, Procure-to-Pay, Record-to-Report, and Plan-to-Produce — and apply that context to ground AI solutions in real enterprise reality.
Work with modern cloud and data platforms including Databricks, SAP Datasphere, SAP HANA Cloud, AWS, Azure, and GCP, gaining hands-on experience with scalable AI workflows.
Collaborate across product, engineering, and business teams to understand how ambiguous business challenges get translated into concrete AI solutions, and contribute meaningfully to that process from early stages through deployment.
Apply machine learning, deep learning, and statistical modeling to build and evaluate AI solutions using real-world enterprise datasets.
What you'll bring
Required Qualifications
Bachelor's or Master's in Computer Science, Applied Mathematics, Statistics, Engineering, or a related quantitative field recent graduates welcome.
2+ years of CS, CE, ML or related field experience work
Foundational understanding of knowledge representation, semantic data systems, or graph databases (through coursework, research, or personal projects).
Familiarity with at least one graph query language (SPARQL, Cypher, or GQL) or a willingness to learn quickly; some exposure to the trade-offs between RDF triple stores and property graph databases is a plus.
Exposure to modern GenAI concepts — RAG, embeddings, vector databases, semantic retrieval — through coursework, research, or hands-on experimentation.
Solid Python and SQL skills; some experience with ML libraries such as PyTorch, TensorFlow, or scikit-learn (academic projects, research work, and personal projects all count).
Eagerness to learn production-grade development practices and grow into operating AI/ML solutions end-to-end.
Clear, collaborative communication style — you ask good questions, explain your thinking, and work well with others.
Preferred Qualifications
Hands-on experience — through internships, research, or projects — with ontology design, semantic modeling, or knowledge graphs.
Any exposure to enterprise software ecosystems (SAP, Salesforce, Workday, ServiceNow, or similar) is a real accelerator here.
Familiarity with the W3C stack (OWL, RDF/RDFS, SKOS, SHACL) or property graph query languages (Cypher, GQL).
Academic or project experience in machine learning and deep learning, including training, evaluating, and improving models on real datasets.
Curiosity about agentic AI, reasoning frameworks, multi-agent architectures, or planning and orchestration.
Experience contributing to shared or reusable codebases — open-source projects, research codebases, or team projects.
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Where you belong
You'll join the Data Labs unit, a tight-knit team turning AI from a promise into something Finance and Spend teams rely on every day, at global scale. You'll work alongside curious engineers, thoughtful product minds, and applied researchers all focused on building AI that customers can trust in the highest-stakes business processes. The problems are real - money, risk, trust, and so is ownership. You'll stretch into new domains, see your models run, and help set the direction for SAP's AI in Finance and Spend. You will learn fast have an excellent opportunity to own things end to end and build foundations others will stand on.
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, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.
Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, age, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability.
Compensation Range Transparency: SAP believes the value of pay transparency contributes towards an honest and supportive culture and is a significant step toward demonstrating SAP’s commitment to pay equity. SAP provides the annualized compensation range inclusive of base salary and variable incentive target for the career level applicable to the posted role. The targeted annual combined range for this position is $106,900 - $229,400 (USD). The actual amount to be offered to the successful candidate will be within that range, dependent upon the key aspects of each case which may include education, skills, experience, scope of the role, location, etc. as determined through the selection process. Any SAP variable incentive includes a targeted dollar amount and any actual payout amount is dependent on company and personal performance. Please reference this link for a summary of SAP benefits and eligibility requirements: SAP North America Benefits.
AI Usage in the Recruitment Process
For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.
Please note that any violation of these guidelines may result in disqualification from the hiring process. Requisition ID: 459718 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid
