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.