Principal Data & Applied Scientist - Ontologies & Semantics

SAP; Palo Alto (CA); On-site; USD 198,000 - 420,000; Full time

Job summary

SAP is building the semantic foundation for AI agents that understand enterprise data and processes. You will design ontologies, implement semantic models, and scale AI capabilities across SAP’s data platforms, aligning with core business semantics and cloud-native workflows.

You will collaborate across product and engineering teams, enabling trusted AI solutions in production while advancing knowledge grounding and data interoperability at enterprise scale.

Qualifications

• 8+ years in knowledge engineering, semantic data systems, applied AI, or data science.
• Master's or PhD in CS, applied math, statistics, engineering, or related field.
• Hands-on experience designing enterprise ontologies and semantic models; proficiency in at least one graph query language (SPARQL, Cypher, or GQL).
• Hands-on experience with GenAI systems including RAG, embeddings, vector databases, and enterprise knowledge grounding.
• Strong Python and SQL skills with production-grade ML libraries and deployment practices.
• Proven track record deploying and operating AI/ML solutions in production and working with cloud environments.

Responsibilities

• Design and maintain enterprise ontologies and semantic models.
• Build AI capabilities including RAG pipelines, embeddings, and vector databases.
• Develop AI solutions using enterprise data, knowledge graphs, and process intelligence.
• Collaborate with product, engineering, and business teams from concept to deployment.
• Apply ML and statistical modeling to real-world enterprise datasets.

Skills

Knowledge engineering

Semantic data systems

Applied AI

Data science

Graph databases

Python

SQL

ML libraries

ML deployment

Cloud platforms

Education

Master's or PhD in CS/Math/Engineering

Tools

SPARQL

Cypher

GQL

Databricks

SAP Datasphere

HANA Cloud

AWS

Azure

GCP

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.

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 Principal Data and Applied Scientist at SAP, you'll 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.

What You'll Build

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 build and scale the layer that makes that possible.

• Design and maintain enterprise ontologies and semantic models that give AI agents accurate, grounded understanding of SAP and connected business landscapes harmonizing data from SAP, various external providers (such as Salesforce, Workday, ServiceNow), and MES/IoT systems into unified semantic layers.
• Build AI capabilities including RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding that make SAP's agents accurate and reliable in production.
• Develop AI capabilities including generative AI and LLM-based solutions using enterprise business data, knowledge graphs, business process intelligence, and other structured and unstructured data assets.
• Leverage SAP's deep data and process context including SAP data models, metadata structures, and business process semantics across Order-to-Cash, Procure-to-Pay, Record-to-Report, and Plan-to-Produce to ground AI solutions in real enterprise reality.
• Work with cloud and data platforms including Databricks, SAP Datasphere, SAP HANA Cloud, AWS, Azure, and GCP to support reliable, scalable AI workflows.
• Partner across product, engineering, business, and customer-facing teams to translate ambiguous business challenges into concrete AI solutions from concept through deployment and continuous improvement.
• Apply machine learning, deep learning, and statistical modeling to develop and evaluate AI solutions using real-world enterprise datasets.

Required Qualifications

• 8+ years of experience in knowledge engineering, semantic data systems, applied AI, or data science in industry, research labs, or advanced academic environments.
• Master's or PhD in Computer Science, Applied Mathematics, Statistics, Engineering, or a related quantitative field
• Hands-on experience designing enterprise ontologies and semantic models; proficiency in at least one graph query language (SPARQL, Cypher, or GQL); understanding of trade-offs between RDF triple stores and property graph databases.
• Hands-on experience with modern GenAI systems RAG, embeddings, vector databases, semantic retrieval, and enterprise knowledge grounding.
• Strong Python and SQL skills with production-grade development practices; experience with ML libraries such as PyTorch, TensorFlow, or scikit-learn.
• Proven track record deploying and operating AI/ML solutions in production including handoff, lifecycle support, and continuous improvement.
• Experience with big data infrastructure and cloud environments Databricks or equivalent, plus at least one major cloud (AWS, Azure, or GCP).
• Excellent communication and stakeholder management skills, with the ability to work cross-functionally in agile environments.

Preferred Qualifications

• Deep working knowledge of SAP data models, metadata structures, and core business processes end-to-end. (SAP knowledge is a strong accelerator)
• Hands-on experience with the SAP data and AI platform stack SAP Datasphere, SAP HANA Cloud Knowledge Graph Engine, SAP Business Data Cloud, SAP One Domain Model, SAP Graph API, and SAP Business Accelerator Hub.
• Deep expertise across the W3C stack (OWL, RDF/RDFS, SKOS, SHACL) and/or property graph query languages (Cypher, GQL).
• Deep expertise in machine learning and deep learning, with experience developing, evaluating, and improving models on real-world datasets.
• Experience with agentic AI, reasoning frameworks, planning, orchestration, tool use, or multi-agent architectures.
• Experience contributing to reusable AI platforms, foundation model initiatives, or shared AI services adopted across multiple product areas.
• Ability to design upper-level and mid-level ontologies aligned with industry standards and apply semantic interoperability frameworks across complex application landscapes.

Where you belong

The Application AI team sits at the foundation layer - We build the LLM systems and intelligent infrastructure that run across SAP's global platforms, which means the work you do here doesn't just influence one product, it sets the direction for how AI operates at enterprise scale. A core part of that challenge is making AI genuinely understand the business not just process text, but reason over richly structured enterprise data through robust data ontologies and semantic knowledge frameworks that give models real context about how SAP's world is organized. This is a team that values engineers who think like owners: people who want to define the architecture, not just implement a spec. You'll work in an environment designed around trust and autonomy, where the expectation is that you move fast, make calls, and drive outcomes without layers of approval slowing you down.

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.

Qualified applicants will receive consideration for employment without regard to ...

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 towards 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 198200-420000USD. 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

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Please note that any violation of these guidelines may result in disqualification from the hiring process.