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You will design and deploy autonomous AI agents using Agentforce to handle complex business scenarios and integrate them with Salesforce workflows. Additionally, you will manage prompt engineering, data grounding, and AI governance to ensure secure and accurate agent performance.
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.
Key Responsibilities
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.
2. 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.
3. 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.
4. 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.
Technical Requirements
● Experience: 4+ years of hands-on Salesforce ecosystem experience (Admin/Developer/Consultant), with at least 1 year of dedicated experience building AI-driven CRM architectures (Agentforce or Einstein Copilot).
● Salesforce Core: Strong understanding of standard automation tools (Flows, Apex, Lightning Web Components) to support custom Agent actions.
● Data Literacy: Solid grasp of Salesforce Data Cloud, data modeling, ingestion, and vector search strategies.
● AI Core Concepts: Deep familiarity with prompt engineering guardrails, LLM reasoning logic, and token optimization.
Preferred Certifications
● Salesforce Certified Agentforce Specialist (AI-201) (Highly Preferred/Mandatory)
● Salesforce Certified AI Associate
● Salesforce Certified Platform App Builder or Platform Developer I (PD1)
● Salesforce Certified Data Cloud Consultant
Soft Skills
● Excellent communication skills with the ability to translate complex AI behavior into clear business logic for stakeholders.
● A strong analytical mindset to look through reasoning traces and continually tune AI responses.
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