Salesforce Agentforce Architect

Key Responsibilities

· Own end-to-end solution architecture across Agentforce, Salesforce CPQ and Revenue Cloud Advanced. · Architect agent-assisted and agentic workflows across opportunity, configuration, pricing, quoting, contracting, ordering and revenue lifecycle processes. · Design agent orchestration patterns, including tool/function calling, workflow delegation, multi-agent patterns, state management and memory. · Architect integration of Agentforce with Salesforce automation, Apex, Flow, APIs, MuleSoft and external enterprise services. · Define appropriate use of LLMs, deterministic logic, workflow engines and traditional automation, rather than defaulting all use cases to generative AI. · Design context engineering and retrieval strategies, including structured/unstructured grounding, retrieval depth, metadata filtering and relevance optimization. · Establish secure agent action patterns using least-privilege access, guardrails, validation, approval checkpoints and human-in-the-loop mechanisms. · Define AI evaluation frameworks covering answer quality, grounding, hallucination, task completion, tool selection, latency and business outcomes. · Establish observability across agent reasoning paths, actions, integration failures, token/credit consumption and operational performance. · Assess model and platform trade-offs across quality, latency, context window, cost, privacy and enterprise constraints. · Architect resilient action layers and transactional integration patterns for revenue processes where consistency and recoverability are critical. · Advise programs on consumption-based economics, AI credit/token optimization and architectural approaches to control run-time cost. · Lead architecture reviews, design authorities and technical governance across global delivery teams. · Mentor technical architects, developers and Agentforce specialists. Required Technical Expertise · Salesforce Agentforce and associated agentic architecture concepts. · Salesforce CPQ and Revenue Cloud Advanced / Revenue Lifecycle Management. · Salesforce Sales Cloud and core platform architecture. · Agent orchestration and tool/function calling. · Multi-agent architectures, delegation and coordination patterns. · Agent state, short/long-term memory and session/context management. · MCP and agent-to-agent interoperability concepts/patterns. · RAG, semantic/vector search, embeddings, chunking and retrieval optimization. · Context engineering beyond basic prompt engineering. · Evaluation frameworks and AI observability. · AI safety, grounding, guardrails and least-privilege action design. · LLM model selection and architectural trade-offs. · Classic NLP concepts including intent classification, entity extraction, semantic similarity and ranking. · Apex, Lightning Platform, Flow, APIs and enterprise integration patterns. · Strong understanding of asynchronous processing, transaction boundaries, resiliency, retries and idempotency. · Security architecture including sharing, CRUD/FLS, permission models and data protection. Preferred Qualifications · 15+ years overall technology experience; 10+ years in Salesforce CPQ / Revenue Cloud architecture. · Proven experience architecting enterprise CPQ / Quote-to-Cash implementations. · Salesforce Application/System/Technical Architect credentials strongly preferred. · Agentforce and Revenue Cloud-related certifications or demonstrable implementation experience. · Experience with MuleSoft and large enterprise integration landscapes preferred. · Ability to communicate architectural decisions to both engineering teams and senior business stakeholders.