Key Responsibilities
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.
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.
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.
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 settings.
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.

📌 Salesforce Agentforce Specialist Chennai
🏢 Zensar
📍 Chennai