Platform Architecture System

Highly skilled Salesforce Agentforce Specialist to lead the design,

implementation, and governance of our autonomous AI agents. In this role, you will transform

our customer service, sales, and operations by building intelligent agents that do not just chat,

but actively execute tasks and workflows.

You will bridge the gap between business requirements and technical AI

orchestration—leveraging Data Cloud, building precise prompts, and designing multi-agent

environments while adhering to strict trust and security standards.

1. Agent Design & Orchestration

● Configure AI Agents: Design and deploy autonomous agents using Agent Studio utilizing Topics, Instructions, and Actions (TIA) to handle complex business scenarios. ● Action & Workflow Integration: Build and connect standard and custom agent actions by integrating Salesforce Flows, Apex actions, and external APIs. ● Multi-Agent Interoperability: Architect agent-to-agent communication protocols and utilize the Model Context Protocol (MCP) and Agent APIs for cross-platform workflows.

1. Prompt Engineering & Grounding

● Prompt Architecture: Author, manage, and optimize scalable prompt templates in Prompt Builder using field generation and flex types. ● Data Grounding: Implement robust grounding techniques using structured and unstructured business data to prevent AI hallucinations and ensure highly relevant agent responses.

1. Data Strategy & Data Cloud

● Data Library Management: Leverage the Agentforce Data Library to feed real-time context to the reasoning engine. ● Retrieval Optimization: Configure Data Cloud retrievers, data chunking, and indexing strategy across keyword, vector, and hybrid search methods.

1. Testing, Lifecycle & Security

● Validation: Use the Agentforce Testing Center and reasoning traces to evaluate, debug, and optimize agent decision intelligence and accuracy before live deployment. ● ALM & Deployment: Manage the application lifecycle of AI models, deploying configurations seamlessly from Sandboxes to Production environments. ● AI Governance: Enforce the Einstein Trust Layer, configure Agent Users secure access permissions, and ensure strict compliance with corporate data security and ethical AI practices