All fields marked * are required
AI / Agentic Solution Architect – Customer Self-Service
Define and drive the AI and agentic architecture for an enterprise Customer Self-Service platform, enabling customers to interact with products, infrastructure, software, services and commercial offerings through intelligent conversational and task-oriented experiences.
The architect will design how AI agents, MCPs, enterprise APIs and workflows work together to help customers perform self-service activities across their lifecycle.
Key Responsibilities
Define the AI and agentic architecture for the Customer Self-Service platform.
Design conversational and task-oriented agents capable of executing end-to-end customer journeys.
Define MCP/tool/API patterns allowing agents to securely interact with enterprise systems.
Design agent orchestration, context management, memory, human-in-the-loop and multi-agent patterns where appropriate.
Enable self-service scenarios such as:
customer onboarding and information collection,
creating and managing change requests,
managing products and solution lifecycle,
fund and commercial consumption management,
usage and consumption analysis,
infrastructure/software/service requests,
guided troubleshooting and customer support.
Integrate AI capabilities with SAP S/4, SAP BTP and other enterprise platforms.
Define authentication, authorization and customer-specific data boundaries for agent actions.
Establish AI governance, guardrails, observability, evaluation and auditability.
Define reusable AI platform capabilities rather than building isolated agents for every use case.
Drive architecture from prototypes through production adoption.
Key Skills
Agentic AI / LLM solution architecture
MCP, tool calling and enterprise API integration
Agent orchestration and workflow design
Conversational AI and customer experience
SAP BTP and enterprise integration
REST / OData / event-driven architectures
Identity, authorization and security
AI governance, guardrails and observability
RAG, context engineering and enterprise knowledge integration
Cloud-native architecture
Preferred Experience
Experience with technologies such as OpenAI, SAP Generative AI Hub / AI Core, MCP, LangGraph/LangChain, Semantic Kernel or comparable agent platforms.
Experience designing enterprise customer portals, digital self-service platforms, subscription/consumption businesses, or B2B customer journeys would be highly valuable.
Required
All fields marked * are required
AI / Agentic Solution Architect – Customer Self-Service
Define and drive the AI and agentic architecture for an enterprise Customer Self-Service platform, enabling customers to interact with products, infrastructure, software, services and commercial offerings through intelligent conversational and task-oriented experiences.
The architect will design how AI agents, MCPs, enterprise APIs and workflows work together to help customers perform self-service activities across their lifecycle.
Key Responsibilities
Define the AI and agentic architecture for the Customer Self-Service platform.
Design conversational and task-oriented agents capable of executing end-to-end customer journeys.
Define MCP/tool/API patterns allowing agents to securely interact with enterprise systems.
Design agent orchestration, context management, memory, human-in-the-loop and multi-agent patterns where appropriate.
Enable self-service scenarios such as:
customer onboarding and information collection,
creating and managing change requests,
managing products and solution lifecycle,
fund and commercial consumption management,
usage and consumption analysis,
infrastructure/software/service requests,
guided troubleshooting and customer support.
Integrate AI capabilities with SAP S/4, SAP BTP and other enterprise platforms.
Define authentication, authorization and customer-specific data boundaries for agent actions.
Establish AI governance, guardrails, observability, evaluation and auditability.
Define reusable AI platform capabilities rather than building isolated agents for every use case.
Drive architecture from prototypes through production adoption.
Key Skills
Agentic AI / LLM solution architecture
MCP, tool calling and enterprise API integration
Agent orchestration and workflow design
Conversational AI and customer experience
SAP BTP and enterprise integration
REST / OData / event-driven architectures
Identity, authorization and security
AI governance, guardrails and observability
RAG, context engineering and enterprise knowledge integration
Cloud-native architecture
Preferred Experience
Experience with technologies such as OpenAI, SAP Generative AI Hub / AI Core, MCP, LangGraph/LangChain, Semantic Kernel or comparable agent platforms.
Experience designing enterprise customer portals, digital self-service platforms, subscription/consumption businesses, or B2B customer journeys would be highly valuable.
Required