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Limited employment up to 6 months (f/m/d) - Enterprise Context Graph & AI (6 Months)
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On-site
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Full-time
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1w ago
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
As a Research Fellow in the Global Content Group (GCG) Engineering team, you will:
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Design and build an Enterprise Context Graph — a graph-based system that captures and persists agentic interactions and the memories derived from them, grounded in the structured enterprise knowledge on which those interactions are based
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Research and prototype approaches for continuous incremental learning, enabling the context graph to evolve and improve from captured interaction histories over time
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Apply ontology engineering methods to model interaction context, agent memory, and knowledge evolution in a semantically rich and queryable graph structure
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Combine data science techniques with ontology design to develop graph-based memory representations that support reasoning, retrieval, and learning
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Collaborate with a global team of software engineers, data scientists, and researchers on cutting-edge challenges at the intersection of agentic AI and knowledge representation
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Document and present your research findings, contributing to publications and internal knowledge-sharing
What you bring
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PhD candidate (mid-to-late stage) or postdoctoral researcher in Computer Science, Data Science, Artificial Intelligence, Computational Linguistics, or a related field
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Deep expertise in ontology engineering and semantic web technologies (RDF, OWL, SPARQL) — you can design, formalize, and reason about complex graph-based knowledge models
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Strong data science background: proven experience with machine learning, embeddings, graph neural networks, or graph-based learning methods
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Solid programming skills in Python; experience with knowledge graph frameworks or ML libraries is a plus
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Research track record in agentic AI systems, memory architectures, continual/incremental learning, or related areas — ideally with publications
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Ability to drive independent research and translate findings into working prototypes
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Good communication skills in English (written and spoken); German is a plus
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Available for a 6-month research fellowship (full-time or part-time)
Where you belong
We build the knowledge backbone of SAP — integrating business data into a unified context graph and delivering AI-powered experiences on top of it. Join a passionate team of engineers and researchers at the forefront of enterprise data management and applied AI.
*Your set of application documents should contain a cover letter, a resume in table form, school leaving certificates, certificate of enrollment, current university transcript of records, copies of any academic degrees already earned, and if available, references from former employers (including internships). Please also describe your experience and skills in foreign languages and computer programs / programming languages. *
*This is a SAP global, strategic, paid, limited placement that provides candidates with opportunities to find purpose in their careers. *
*#SAPNext Gen *
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.
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: 447176 | Work Area: Administration | Expected Travel: 0 - 10% | Career Status: Graduate | Employment Type: Limited Full Time | Additional Locations: #
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SAPについて

SAP
PublicThe best-run businesses run SAP.
10,001+
従業員数
Walldorf
本社所在地
$157B
企業価値
レビュー
3.9
10件のレビュー
ワークライフバランス
3.2
報酬
3.5
企業文化
4.1
キャリア
3.4
経営陣
3.3
72%
友人に勧める
良い点
Good benefits and retirement plans
Training and development opportunities
Supportive team collaboration
改善点
Work-life balance challenges
High workload and stress during peak times
Limited career advancement opportunities
給与レンジ
2件のデータ
L3
L4
L5
Intern
L3 ·
0件のレポート
-
年収総額
基本給
-
ストック
-
ボーナス
-
面接体験
5件の面接
難易度
4.0
/ 5
期間
14-28週間
体験
ポジティブ 0%
普通 40%
ネガティブ 60%
面接プロセス
1
Application Review
2
HR/Recruiter Screen
3
Phone/Technical Screen
4
Hiring Manager Interview
5
Onsite/Panel Interview
6
Technical Assessment
よくある質問
Technical Knowledge
Coding/Algorithm
Behavioral/STAR
Past Experience
SAP-Specific Technical Skills
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