Job Description

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 do:

We are seeking a Data Scientist focused on AI integration to help embed machine learning and generative AI capabilities directly into our web delivery platforms. This role bridges data science, software engineering, and product delivery, translating AI opportunities into scalable features used by real customers. The ideal candidate combines strong machine learning expertise with practical engineering skills and can collaborate closely with web developers, product owners, and platform teams to deploy AI-driven capabilities into production environments. This is a hands-on role.

You will work with a team responsible for managing all systems and operations for our cloud-based web solutions. You will work with a globally distributed and diverse team whose mission is to delivery highly available world-class web solutions. We run SAP.com.

You won't just be "chatting" with bots. You'll be building the cognitive infrastructure of our company. If you think in terms of "chains of thought" and live for a perfectly optimized embedding space, this is your team.

Your key responsibilities will be:

• Design and implement AI-powered capabilities within our web delivery ecosystem.
• Integrate machine learning models, LLMs, and predictive systems into web applications and APIs.
• Partner with engineering teams to move models from experimentation to production-ready services.

• Architect Agentic Workflows: Design and implement stateful, multi-agent systems using LangChain and LangGraph to automate complex, multi-step business processes.

• Develop and evaluate machine learning models for use cases such as:
• personalization and recommendation
• predictive analytics
• content generation
• user behavior modeling
• anomaly detection
• Run experiments and measure impact on key product and user metrics.

• Prototype and deploy LLM-powered features such as intelligent assistants, automated workflows, or content generation.
• RAG Optimization: Develop and refine RAG architectures, focusing on advanced chunking strategies, semantic caching, and hybrid search (Vector + Keyword) to minimize hallucinations
• Design prompt strategies, evaluation pipelines, and guardrails.
• Optimize inference performance and cost for production systems.

• Work closely with web delivery and platform engineering teams to integrate AI into existing architecture.
• Develop APIs, services, or microservices that expose AI functionality.
• Ensure models are scalable, observable, and maintainable.

• Define and implement data pipelines required for training and inference.
• Collaborate with data engineering to ensure high-quality, well-governed datasets.
• Establish best practices for model lifecycle management.

• Implement responsible AI practices including bias monitoring, explainability, and performance tracking.
• Maintain reproducible experimentation and documentation.

You will report to the head of development & engineering for Digital Platforms within the Demand Generation organization of Corporate Processes and Information Technology (CP&IT).

What you bring:

You bring a desire to learn, to share, to be impactful. You will strengthen this team with your deep technical knowledge and work alongside other technical experts to deliver the best digital experience for our customers.

You bring an attitude that is willing to take on all challenges, puts team first, and is open to new ideas including looking for new ways to utilize AI to further improve our digital platforms.

Core job requirements:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or related field
• 3+ years of experience building and deploying machine learning models
• Strong programming skills in Python
• Experience with ML frameworks such as:
  • PyTorch
  • TensorFlow
  • LangChain/LangGraph
• Experience integrating models into production systems or APIs
• Familiarity with cloud environments (AWS, Azure, or GCP)
• Experience with data pipelines and feature engineering
• Experience with vector databases
• Proficiency with OpenAI SDK, Anthropic, and local inference via vLLM or Ollama
• Experience with Docker and Kubernetes for containerized model deployment.
• Proficient communicating in English; secondary language is a plus but not required
• Willingness to learn more technical knowledge.

Meet your team:

Our team is made up of some of the best technologists in the field all with a desire to deliver world class web solutions. We are a delivery unit; we spend more time coding than building slides. We love to research new technologies, to innovate, and to look at new ways to amaze our customers.

We make each other better by sharing knowledge and challenging each other as technology evolves and the team matures.

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, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.

Successful candidates might be required to undergo a background verification with an external vendor.

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: 447265 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid