Principal Product Manager - AI Data

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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. 

 

 

About Us:  

BDC is a forward-thinking AI organization dedicated to innovation, engineering excellence and customer satisfaction. We are committed to delivering harmonized data (SAP and Non-SAP) and analytical insights in intelligent apps that deliver quantifiable business outcomes to our customers. BDC data products are core to our strategy and serve as the foundation for trusted, connected, and actionable enterprise data. We are looking for a hands-on Principal Product Manager - AI Data to leading the definition and delivery of key AI innovations in BDC portfolio.  

   

Role Overview:  

We are looking for a Principal Product Manager - AI Data with a strong background in AI to define and drive the product roadmap and execution of core capabilities such as data product generation and management, data quality, master data management, planning, analytics and visualization. The candidate will have experience working on Knowledge Graph, semantic search, ontologies, prompt engineering and RAG. You will collaborate closely with cross-functional teams, including product, engineering and data science teams, to provide exceptional value and drive business growth.  

   

Key Responsibilities:  

   

Strategic Leadership:  

• Define and deliver the roadmap for AI first capabilities in alignment with the Business Data Cloud and company objectives. 

• Champion the role of the BDC Knowledge Graph as one of the core components for data product and master data management 

• Work with partners where possible to enhance overall BDC capabilities 

• Define and deliver persona centric solutions that leverage SAP AI, SAP Databricks and other partner capabilities.  

• Champion the harmonized product operating model (HPOM) and product-led growth approach, ensuring that product decisions are driven by data and customer insights.  

   

 AI and Data Expertise:  

• Shape BDC’s AI strategy by ensuring the Knowledge Graph supports scalable ML/AI foundations and intelligent workflows. 

• Own end to end product lifecycle for AI enabled features including strong background of data preparation for ML, AI platforms and foundational models and data centric tooling. 

• Stay ahead of market trends in AI, knowledge graphs, and enterprise data to inform strategy and competitive positioning. 
   

 Data-Driven Product Development:  

• Leverage your strong background in data engineering to guide the development of AI capabilities.  

• Utilize data analytics and metrics to inform product decisions, track performance, and optimize customer outcomes.  

 

Team Empowerment:  

• Lead and mentor empowered product teams, fostering a culture of ownership, accountability, and continuous improvement.  

• Drive innovation and experimentation across PM, UX, and development teams to explore new opportunities and solve complex problems.   

   

Stakeholder Management:  

• Build strong relationships with key stakeholders, including BDC and SAP leadership, SAP AI, SAP LOBs, customers, and key strategic partners (such as SAP Databricks), to ensure alignment and support for product initiatives.  

• Communicate product vision, strategy, and progress to stakeholders, providing transparency and managing expectations.  

• Act as a spokesperson for the product, representing the company at industry events, conferences, and customer meetings, as required.  

   

Continuous Improvement:  

• Stay current with industry trends, emerging technologies, and best practices in product management and data engineering.  

• Implement and refine processes that enhance the efficiency, quality, and impact of the product development lifecycle.