Description:
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.
What You'll Build
- In this role, you'll define the architecture for intelligent, enterprise-grade applications and platforms with AI built into the core design rather than added as an afterthought.
- You'll shape end-to-end solutions across application services, integration layers, data architecture, event-driven systems, security, and AI/ML components. That includes designing patterns for model integration, batch and real-time inference, feature and data pipelines, vector search, LLM orchestration, agent frameworks, evaluation services, and responsible AI controls.
- You’ll guide teams on scalability, resilience, interoperability, observability, privacy, and compliance, and ensure architecture choices support both near-term delivery and long-term platform evolution.
- Your work will directly influence how quickly engineering teams can build, govern, and scale AI-enabled capabilities across products and customer scenarios.
What You Bring
- You bring deep expertise in software architecture for large-scale distributed systems, including microservices, event-driven patterns, APIs, integration layers, and data platforms
- You have a strong understanding of AI and ML system architecture, including training pipelines, inference layers, model lifecycle design, and ML platform capabilities
- You have experience designing enterprise-grade generative AI solutions using LLMs, embeddings, vector databases, RAG patterns, tool use, and orchestration frameworks
- You are skilled at designing scalable and secure application architectures that integrate transactional systems, analytical platforms, and AI-powered services
- You have strong knowledge of cloud-native architecture, including containers, Kubernetes, infrastructure automation, observability, resilience, and performance engineering
- You have experience defining reference architectures, design standards, and reusable technical patterns for AI-enabled product development
- You bring a strong understanding of data architecture, governance, metadata, privacy, and access patterns required to support trustworthy AI solutions
- You evaluate build-versus-buy decisions across models, platforms, data services, and integration tooling, clearly articulating technical and business trade-offs
- You have knowledge of responsible AI, model governance, security controls, compliance requirements, and architectural guardrails for safe enterprise adoption
- You have experience leading architecture reviews, influencing engineering roadmaps, and aligning technical direction across multiple teams or product areas
- You communicate complex architectural decisions clearly to engineers, product leaders, and executive stakeholders