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.

📌 Salesforce Agentforce Specialist (Chennai)
🏢 Zensar
📍 Chennai