Principal Data and Applied Science, Finance and Spend Autonomous Suite, Palo Alto

SAP
Palo Alto
Workplace: HybridFull timeUSD 198,200 - 420,000 annuallyFunction: Finance & AccountingExperience: 8+ yearsEducation: phdSkills: ["Communication","Stakeholder management","Cross-functional collaboration","Agile collaboration"]

Build the semantic and contextual foundation that makes SAP’s AI agents accurate and enterprise-ready for Finance and Spend processes. You’ll design enterprise ontologies and semantic models, develop GenAI and LLM-based solutions (including RAG, embeddings, and vector databases), and ground them in SAP data, metadata, and knowledge graphs. Work with cloud/data platforms (Databricks, SAP Datasphere, SAP HANA Cloud, AWS/Azure/GCP) and partner cross-functionally to deploy and continuously improve production AI.

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SAP
SAP
2 hours ago

Principal Data and Applied Science, Finance and Spend Autonomous Suite, Palo Alto

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Last checked: 2 hours agoStatus: Live

Job Summary

Build the semantic and contextual foundation that makes SAP’s AI agents accurate and enterprise-ready for Finance and Spend processes. You’ll design enterprise ontologies and semantic models, develop GenAI and LLM-based solutions (including RAG, embeddings, and vector databases), and ground them in SAP data, metadata, and knowledge graphs. Work with cloud/data platforms (Databricks, SAP Datasphere, SAP HANA Cloud, AWS/Azure/GCP) and partner cross-functionally to deploy and continuously improve production AI.
Location: Palo Alto
Workplace: Hybrid
Employment Type: Full time
Job Function: Finance & Accounting
Seniority: Sr. Manager level

Key Responsibilities

  • •Design and scale semantic and contextual foundations that enable accurate, grounded SAP AI agents.
  • •Develop and maintain enterprise ontologies, semantic models, and unified semantic layers across SAP and connected business systems.
  • •Build AI capabilities including RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding for reliable production behavior.
  • •Develop GenAI and LLM-based solutions using enterprise data, knowledge graphs, business process intelligence, and structured/unstructured assets.
  • •Apply machine learning, deep learning, and statistical modeling to develop, evaluate, and continuously improve AI solutions using 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 graph query language proficiency (SPARQL, Cypher, or GQL).
  • •Hands-on experience with modern GenAI systems including RAG, embeddings, and vector databases for enterprise knowledge grounding.
  • •Strong Python and SQL skills and experience deploying AI/ML solutions in production with continuous improvement.
Experience:8+ years
Education:PhD / Doctorate in Computer Science, Applied Mathematics, Statistics, Engineering, or related quantitative field
Skills:CommunicationStakeholder managementCross-functional collaborationAgile collaboration
Tech Stack:PythonSQLPyTorchTensorFlowScikit-learnRAGEmbeddingsVector databasesSPARQLCypherGQLRDFRDFSOWLSKOSSHACLDatabricksSAP DatasphereSAP HANA CloudSAP HANA Cloud Knowledge Graph Engine

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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