Principal Data and Applied Science, SCM Autonomous Suite, Palo Alto (Palo Alto, CA, US, 94304)

SAP
Palo Alto
Workplace: HybridFull timeUSD 198,200 - 420,000 annuallyFunction: Communications, PR & CommunityExperience: 8+ yearsEducation: mastersSkills: ["Communication","Stakeholder management","Cross-functional collaboration"]

Build and scale the semantic foundation that powers SAP’s enterprise-ready AI agents for supply-chain execution and planning. Design and maintain ontologies and semantic models, develop RAG and vector-based knowledge grounding, and create production-grade generative and LLM-based solutions. Apply machine learning and statistical modeling on real enterprise datasets while partnering with product, engineering, and customer-facing teams across the concept-to-deployment lifecycle.

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FursaFursa
SAP
SAP
2 hours ago

Principal Data and Applied Science, SCM Autonomous Suite, Palo Alto (Palo Alto, CA, US, 94304)

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Last checked: 2 hours agoStatus: Live

Job Summary

Build and scale the semantic foundation that powers SAP’s enterprise-ready AI agents for supply-chain execution and planning. Design and maintain ontologies and semantic models, develop RAG and vector-based knowledge grounding, and create production-grade generative and LLM-based solutions. Apply machine learning and statistical modeling on real enterprise datasets while partnering with product, engineering, and customer-facing teams across the concept-to-deployment lifecycle.
Location: Palo Alto
Workplace: Hybrid
Employment Type: Full time
Job Function: Communications, PR & Community
Seniority: Mid level

Key Responsibilities

  • •Design and scale the semantic and contextual foundation that enables SAP’s AI agents to understand enterprise business master data, process flows, and relationships.
  • •Build and maintain enterprise ontologies and semantic models, harmonizing data across SAP, Salesforce, Workday, ServiceNow, MES/IoT, and external providers into unified semantic layers.
  • •Develop AI capabilities including RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding for accurate, reliable agent outputs in production.
  • •Develop generative AI/LLM-based solutions using enterprise business data, knowledge graphs, business process intelligence, and structured/unstructured data assets.
  • •Apply machine learning, deep learning, and statistical modeling to develop, evaluate, deploy, and continuously improve AI solutions for real-world enterprise datasets.
Travel: Low travel

Pay and Benefits

Salary: USD 198,200 - 420,000 annually

Key Requirements

  • •8+ years of experience in knowledge engineering, semantic data systems, applied AI, or data science.
  • •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, including a graph query language (SPARQL, Cypher, or GQL) and trade-offs between RDF triple stores and property graph databases.
  • •Hands-on experience with GenAI systems such as RAG, embeddings, vector databases, semantic retrieval, and enterprise knowledge grounding.
  • •Strong Python and SQL skills with production-grade development practices and ML libraries (PyTorch, TensorFlow, or scikit-learn).
Experience:8+ years
Education:Master's in Computer Science, Applied Mathematics, Statistics, Engineering, or a related quantitative field
Skills:CommunicationStakeholder managementCross-functional collaboration
Tech Stack:PythonSQLRDFRDFSSKOSSHACLOWLSPARQLCypherGQLRAGEmbeddingsVector databasesPyTorchTensorFlowScikit-learnDatabricksSAP DatasphereSAP HANA CloudAWS

Company Brief

SAP
Global enterprise software company best known for ERP systems and business applications covering finance, supply chain, procurement, HR, analytics, and customer management for large organizations.
Industry: Enterprise Software
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Walldorf, Germany
Founded: 1972
Glassdoor
Glassdoor: 4.1
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