AI Solution Architect - Generative & Agentic AI (SAP BTP)

About the role

SAP is looking for an experienced AI Solution Architect to lead the design and delivery of enterprise-scale Generative AI and Agentic AI solutions on SAP Business Technology Platform (BTP). Based in the Customer Engagement & Adoption (CE&A) Global Delivery Hub, the role helps global customers accelerate AI adoption across SAP landscapes, combining customer engagement, solution architecture ownership and hands-on technical leadership.

Key responsibilities

• Engage with customer stakeholders to define AI strategy, architecture and measurable business outcomes.
• Lead discovery sessions and workshops to shape enterprise AI adoption journeys.
• Architect scalable, secure, enterprise-grade GenAI and Agentic AI solutions, including reference architectures for RAG, multi-agent orchestration, A2A, MCP and hybrid AI patterns.
• Establish best practices for AI architecture covering governance, scalability, security and lifecycle management.
• Design and guide implementation of LLMOps/MLOps pipelines and evaluate and select LLMs, agent frameworks and AI platforms.
• Drive customer adoption from proof of concept through enterprise-wide rollout, ensuring responsible AI, compliance, performance and cost efficiency.
• Mentor engineering and data science teams and contribute reusable accelerators and solution assets.

Required profile

• 8-20 years of experience in AI/ML and solution architecture, including enterprise delivery.
• Bachelor's or Master's degree in Computer Science, Engineering, Data Science or a related field.
• Strong customer-facing communication and proven ability to lead technical strategy and influence enterprise decisions.
• Location: preferably Sydney, Brisbane, Melbourne or Canberra, with openings in Malaysia and the Philippines; a valid work permit is required, and visa sponsorship is not provided.

Required skills

• Generative AI architectures (RAG, agent orchestration, model customization) and agentic systems (multi-agent coordination, A2A/MCP).
• Frameworks such as LangChain, LangGraph, CrewAI or equivalent.
• Python (proficiency); JavaScript/TypeScript is beneficial.
• Vector databases, semantic retrieval and knowledge graphs; MLOps/LLMOps and model lifecycle governance.
• SAP BTP preferred; SAP S/4HANA, HANA DB and SAP AI offerings are advantageous.