SAP BTP Developer - AI Expert
Role details
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Tech stack
Job description
As an experienced SAP Lead for AI and Clean Core, you will play a key role in connecting enterprise transformation with practical, AI-driven innovation across SAP landscapes. In this role, you will help clients unlock the value of SAP by applying AI capabilities-such as SAP Joule, SAP AI Core, SAP Business AI, Azure OpenAI, GPT models and Accenture's own AI tools-to automate document processing, enhance decision-making with predictive insights, enable natural language queries against SAP data, and create intelligent user experiences across SAP S/4HANA and BTP. You will ensure all this happens within a Clean Core SAP landscape, using standard APIs, side-by-side extensions, and modern integration patterns to preserve upgradability and robustness. Combining strategic consulting with hands-on solution design and delivery, you will work directly with business and IT stakeholders, shape AI roadmaps, and guide teams in implementing real, measurable AI outcomes-not just concepts.
What's in it for you?
- You will have the opportunity to work with some of the biggest companies globally designing and delivering SAP-led complex transformational programs, enhancing new skills in SAP and in Program & Solution Governance
- This an opportunity to join a European team of senior SAP experts with a focus on "thought leadership, origination, sales and delivery of large transformation SAP programs across industries"
- Work at the leading edge of SAP + AI, leveraging tools like SAP Joule, SAP AI Core, SAP Business AI, Azure OpenAI, and GPT models on real client projects.
- Drive Clean Core-aligned AI solutions, influencing technical architecture and extension strategies that keep SAP landscapes future-ready and upgrade-safe
- Influence strategic decisions on AI adoption roadmaps, data and integration architecture, and Clean Core transformation initiatives at CxO and program leadership level., * Advise clients on high-value AI and GenAI use cases within their SAP landscapes, prioritizing opportunities in intelligent automation, predictive analytics, and enhanced user experiences.
- Design and implement AI-powered solutions using SAP AI technologies (e.g., SAP Joule, SAP AI Core, SAP AI Business Services such as Document Information Extraction) integrated with SAP S/4HANA, SAP BTP, and relevant SAP modules.
- Ensure all AI implementations follow Clean Core principles by using public APIs, events, and side-by-side extensions on BTP, avoiding core modifications and minimizing technical debt.
- Conduct AI readiness and maturity assessments of SAP landscapes, covering data quality, integration points, security, and architecture requirements for ML and GenAI.
- Lead design thinking sessions, client workshops, and requirement-gathering meetings to translate business challenges into clear AI solution designs and roadmaps.
- Create and own proof-of-concepts, MVPs, and production-grade AI solutions that demonstrate tangible outcomes such as reduced processing time, higher accuracy, or improved user satisfaction.
- Mentor and coach client teams / Internal teams and junior consultants on AI/ML fundamentals, GenAI best practices, SAP AI capabilities, and Clean Core-friendly extension patterns.
- Stay current with SAP's AI roadmap, broader AI ecosystem trends, and industry-specific innovations, actively sharing insights and driving internal innovation initiatives
Requirements
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Extensive SAP consulting experience spanning the full project lifecycle (requirements, solution design, configuration/development, testing, deployment, and support).
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Demonstrable, hands-on experience implementing or consulting on AI/ML or GenAI solutions in enterprise SAP environments.
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Strong understanding of SAP BTP (extensions, integration, security) and Clean Core transformation principles.
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Practical knowledge of SAP AI capabilities such as SAP Joule, SAP AI Core, and SAP AI Business Services.
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Experience working with generative AI technologies and LLMs (e.g., GPT, Claude), including basic prompt engineering, RAG (Retrieval-Augmented Generation), and common integration patterns with enterprise systems.
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Demonstrated ability to translate business needs into technical AI solutions, with strong problem-solving skills and a structured consulting approach.
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Excellent client-facing and communication skills, with the ability to explain complex AI and data concepts in simple, business-friendly language.
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Exposure to AI governance and responsible AI frameworks, including risk assessment, explainability, and fairness considerations Nice to have:
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Experience with cloud AI platforms such as Azure AI, AWS SageMaker, or Google Vertex AI.
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Understanding of vector databases and semantic search technologies for RAG and intelligent document retrieval scenarios.
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Working knowledge of Python, R, or similar data science languages for prototyping, data manipulation, and simple model experimentation
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AI governance (security, data privacy, risk assessment, explainability), with experience applying these in regulated or enterprise environments