NTT DATA is seeking a skilled Salesforce CPQ Architect to lead end-to-end solution architecture for Agentforce, Salesforce CPQ, and Revenue Cloud Advanced. The role involves designing complex agent-assisted and agentic workflows across the entire revenue lifecycle, including opportunity management, configuration, pricing, quoting, contracting, and ordering.

This position requires expertise in designing agent orchestration patterns, integrating Agentforce with Salesforce automation tools like Apex and Flow, and leveraging APIs and MuleSoft for external enterprise service integrations. A key aspect is defining appropriate uses of LLMs and other automation techniques, avoiding over-reliance on generative AI. The architect will also focus on designing context engineering and retrieval strategies, establishing secure agent action patterns, and defining AI evaluation frameworks.

Furthermore, the role involves establishing observability across agent reasoning, actions, and integration failures, assessing model and platform trade-offs, and architecting resilient action layers for critical revenue processes. The ideal candidate will advise on consumption-based economics, AI credit optimization, and architectural approaches for cost control, while also leading architecture reviews and mentoring technical teams.

Architect agent-assisted and agentic workflows across the opportunity, configuration, pricing, quoting, contracting, and revenue lifecycle. Design agent orchestration patterns, including tool/function calling, workflow delegation, and multi-agent coordination. Integrate Agentforce with Salesforce automation tools, Apex, Flow, APIs, MuleSoft, and external enterprise services. Define and implement strategies for context engineering and retrieval, including grounding and relevance optimization. Establish secure agent action patterns with least-privilege access and human-in-the-loop mechanisms. Develop AI evaluation frameworks covering task completion, tool selection, and business outcomes. Implement observability across agent reasoning paths, actions, and operational performance. Advise on AI credit optimization and architectural approaches to manage run-time costs. Lead architecture reviews, design authorities, and technical governance for global delivery teams. Mentor technical architects, developers, and Agentforce specialists.

Possess deep expertise in Salesforce Agentforce and agentic architecture concepts, alongside comprehensive knowledge of Salesforce CPQ and Revenue Cloud Advanced. Demonstrate proficiency in Salesforce Sales Cloud and core platform architecture, as well as agent orchestration and tool/function calling. Experience with multi-agent architectures, delegation, and coordination patterns is essential. Solid understanding of agent state, memory management, and context management is required. Familiarity with RAG, semantic search, embeddings, chunking, and retrieval optimization techniques is crucial. Proficiency in context engineering beyond basic prompt engineering is expected. Experience with evaluation frameworks and AI observability is necessary. Knowledge of AI safety, grounding, guardrails, and least-privilege action design is vital. Familiarity with LLM model selection and architectural trade-offs is required. Understanding of classic NLP concepts such as intent classification, entity extraction, and semantic similarity is important. Proficiency in Apex, Lightning Platform, Flow, APIs, and enterprise integration patterns is a must. Strong grasp of asynchronous processing, transaction boundaries, resiliency, retries, and idempotency is essential. Experience with security architecture, including sharing, CRUD/FLS, permission models, and data protection, is required. Preferred qualifications include 15+ years of technology experience with 10+ years in Salesforce CPQ/Revenue Cloud architecture, proven enterprise CPQ/Quote-to-Cash implementation experience, and Salesforce Architect credentials.