Job Summary

The context engine that makes AI enterprise ready.

Responsibilities

As part of our Data and Applied Science team, 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.

The Data and Applied Science team will 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. Your team will build and scale the layer that makes that possible.

Requirements for this position include the following:

- 10+ years proven experience leading, mentoring, and growing high-performing teams of data scientists, machine learning engineers, and AI practitioners, with a robust track record of driving complex AI initiatives from concept to production across multiple teams and stakeholders.

- Ability to define technical strategy, establish team priorities, and align AI investments with business objectives, product roadmaps, and customer outcomes.

- Experience building a culture of technical excellence, operational rigor, and continuous learning.

- Excellent stakeholder management and executive communication skills, with the ability to influence senior leadership and translate technical concepts into business value.

- 5+ years of people management experience leading data science and AI teams,



with demonstrated success hiring, coaching, and retaining top AI talent.

- Proven experience delivering large-scale AI programs across multiple teams and business units and partnering with senior executives to define AI strategy and investment priorities.

Desirable Skills

- Experience leading globally distributed teams and cross-organizational AI initiatives, including managing budgets, hiring plans, vendor relationships, and strategic partnerships.

- Experience defining AI adoption strategies, measuring business impact through KPIs, and establishing reusable enterprise AI platforms, governance frameworks, and shared services across multiple product areas.

- Thought leadership demonstrated through patents, publications, conference presentations, open-source contributions, or industry recognition in AI, knowledge graphs, semantic technologies, or enterprise intelligence.

- Knowledge of SAP's domains, data models, metadata structures and core business processes end-to-end.

- 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.

Key Knowledge and Abilities

- AI Platform, Architecture Governance

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Data Science Leader, CX (Bengaluru)
🏢 Classic Marble
📍 Bengaluru