AgentForce Solutions Architect
New
L
ListEngageDigital Transformation
USA, RemoteFull-TimeMiddle
SalaryCompetitive salary and performance-based incentives
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Job Details
- Experience
- 3+ years of development and configuration experience within Salesforce Platform
- Required Skills
- PythonJavascriptRESTful APIsPrompt EngineeringLLM
Requirements
- 3+ years of development and configuration experience within Salesforce Platform
- Hands-on experience building and deploying Agentforce agents in production environments
- Expertise in Salesforce Flow (including autonomous mode flows) and Apex for custom agent actions
- Experience with API development and integration, including designing and consuming RESTful APIs via MuleSoft or native Salesforce
- Proficiency in prompt engineering and working with Large Language Models (GPT-4, Claude, etc.)
- Experience with Data Cloud or similar customer data platforms
- Knowledge of programming languages such as JavaScript, Python, and/or Apex
- Understanding of AI/ML concepts, retrieval-augmented generation (RAG), and grounding techniques
- Experience with agent testing methodologies and conversation design principles
- Salesforce Administrator certification
- AgentBlazer Champion certification
- Platform Developer I certification
Responsibilities
- Design, develop, test, and deploy autonomous AI agents using Salesforce Agentforce across Salesforce clouds
- Build and configure custom Agent Actions (Flows, Apex, Prompt Templates, MuleSoft APIs) to extend agent capabilities
- Design and implement agent topics, instructions, and guardrails to ensure accurate and safe agent responses
- Create proof of concepts (POCs) to evaluate agent feasibility and demonstrate business value before full implementation
- Develop custom Prompt Templates and engineer system prompts for optimal agent performance
- Integrate agents with Data Cloud, external systems, and third-party LLMs using MuleSoft or APIs
- Implement agent security, including Einstein Trust Layer configuration and data masking
- Perform comprehensive testing including unit testing, simulation testing, and support user acceptance testing (UAT)
- Monitor agent performance analytics and continuously optimize based on conversation metrics
- Troubleshoot and resolve issues related to agent responses, actions, and integrations
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