AI Architect

About the role

As an AI Architect at SAP you will define the architecture for intelligent, enterprise‑grade applications where AI is embedded from day one. You will work across multiple layers – from data and integration to security and AI/ML components – to enable scalable, resilient, and compliant AI solutions for our global customers.

Key responsibilities

• Design end‑to‑end architectures for AI‑enabled platforms, including model integration, batch and real‑time inference, feature pipelines, vector search, LLM orchestration and responsible AI controls.
• Guide engineering teams on scalability, resilience, interoperability, observability, privacy and compliance.
• Define reference architectures, design standards and reusable patterns for AI product development.
• Evaluate build‑versus‑buy decisions for models, platforms and data services, articulating technical and business trade‑offs.
• Lead architecture reviews, influence roadmaps and ensure alignment with long‑term platform evolution.

Required profile

• Deep expertise in software architecture for large‑scale distributed systems (microservices, event‑driven patterns, APIs, integration layers, data platforms).
• Strong understanding of AI/ML system architecture, including training pipelines, inference layers, model lifecycle and ML platform capabilities.
• Experience designing enterprise‑grade generative AI solutions using LLMs, embeddings, vector databases, RAG patterns and orchestration frameworks.
• Proficiency in cloud‑native architecture (containers, Kubernetes, infrastructure automation, observability, resilience, performance engineering).
• Knowledge of data architecture, governance, metadata, privacy and access patterns for trustworthy AI.
• Familiarity with responsible AI, model governance, security controls and compliance requirements.

Required skills

• Microservices
• Event‑driven architecture
• APIs & integration layers
• Data platforms
• AI/ML pipelines & model lifecycle
• ML platform capabilities
• Generative AI, LLMs, embeddings
• Vector databases
• Retrieval‑Augmented Generation (RAG)
• Orchestration frameworks
• Cloud‑native architecture
• Containers
• Kubernetes
• Infrastructure automation
• Observability & performance engineering
• Data governance & metadata management
• Privacy & security controls
• Responsible AI & compliance

What we offer

• Continuous learning and skill growth opportunities
• Comprehensive benefits package
• Supportive team focused on wellbeing and inclusion
• Chance to shape AI strategy for a global enterprise software leader