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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal AI Architect - CTO Industry AI - **Company:** SAP AG - **Location:** Garching bei München, Germany - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Architectural Patterns, Cloud Engineering, Cyber Security, Continuous Integration, Data Governance, Distributed Systems, Graph Database, Software Architecture, Azure Machine Learning, SAP (Applications), SAP Business Suiteing, Software Engineering, Systems Integration, Feature Store, Feature Engineering, Data Ingestion, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, AI Platforms, Information Technology, Machine Learning Operations, Drift Detection - **Published:** October 14, 2026 - **Apply:** https://www.careerjet.de/jobad/de3e2b4ecd6e550e0c05e4c00f277fb752 ## About the Role * Demonstrated ability to define architectural guardrails and govern their adoption across engineering teams working in parallel. * Hands-on experience architecting and operating mission-critical ML platforms end-to-end - from data ingestion and feature engineering through model deployment, monitoring, and drift detection. * Deep knowledge of cloud-native MLOps: model registries, feature stores, CI/CD pipelines, observability stacks, canary and blue-green deployments, and infrastructure as code. * Practical experience integrating LLMs, RAG, and multi-agent systems into enterprise production architectures - including context engineering, semantic retrieval, agentic orchestration, and evaluation harness design. * Strong security architecture fluency: ability to design for compliance with regulatory and data governance requirements across cloud environments. * Experience leading architectural reviews, mentoring engineers on design tradeoffs, and communicating architectural reasoning clearly to both technical teams and non-technical stakeholders. * Comfort with specification-led engineering: the ability to decompose ambiguous problems, write precise architectural specifications, and hold the bar during implementation. * 7-10 years of professional experience in software architecture, platform engineering, or AI/ML systems roles, preferably in cloud or enterprise SaaS. * Bachelor's degree in Computer Science, Software Engineering, or a related discipline; advanced degree is a plus. * Domain fluency in one or more SAP-relevant areas (supply chain, manufacturing, asset management, procurement) is a strong plus. ## 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 do: The Office of the CTO (oCTO) for IndustryAI sits at the intersection of the SAP Business AI Platform (BAIP), Industry Product & Engineering, the LoB application teams, and FDE engagements with strategic customers. The Architecture team inside oCTO does not own architecture strategy for any single industry or LoB - that lives with the product and engineering organizations. What we own is the AI-native and agentic architecture strategy for IndustryAI: how systems are designed to be secure, scalable, and observable; which patterns get standardized; and how the architectural foundation is built and governed so industry and LoB products can ship AI reliably. As Principal AI Architect, you lead architectural direction for one or more capability areas end-to-end. You define target and reference architectures for large-scale AI-native and ML platforms, run architectural validation with engineering teams and strategic customers through FDE, and ensure proven designs are standardized into reusable patterns across IndustryAI. You make architectural decisions independently, mentor senior engineers on design choices, and serve as a credible technical partner to product management, data science, and platform leadership. In this role you will: * Define target and reference architectures for AI-native systems and ML platforms within your capability area - aligned with SAP standards, security requirements, and product objectives. * Act as a technical authority across BAIP, Industry Product & Engineering, LoB, and FDE for your area - align engineering stakeholders, govern architectural guardrails, and drive adoption through influence rather than reporting lines. * Lead specification-driven engineering: decompose ambiguous problems into architecturally sound designs, validate decisions against guardrails, and ensure consistent adoption of CI/CD, MLOps, and responsible AI practices. * Guide complex initiatives from proof-of-concept to enterprise-grade production - integrating LLMs, retrieval-augmented generation (RAG), multi-agent systems, and knowledge graph platforms into scalable, observable architectures. * Standardize reusable architectural patterns and libraries across IndustryAI, turning one-off technical solutions from FDE engagements into documented, adoptable reference architectures for engineering teams. * Contribute concrete architectural requirements to BAIP - orchestration topology, memory and context architecture, inference infrastructure, evaluation harnesses, observability stacks, and guardrails - grounded in what capability areas actually need to ship reliably. * Oversee architectural reviews within your scope: validate designs before commitment, identify risks early, and ensure compliance with global security, privacy, and data governance requirements. * Stay current with the external technology landscape - evaluate emerging approaches in agentic AI, semantic retrieval, knowledge graphs, cloud-native MLOps, and distributed systems, and translate that signal into concrete architectural recommendations. * Mentor senior engineers and development architects on design decisions, specification quality, and the reasoning behind architectural tradeoffs. * Partner with product management, data science, and platform engineering to translate product objectives into technically sound, measurable system designs with clear SLIs and SLOs.