Jr Salesforce QA

Job Title: Jr Salesforce QA
Location: Pleasanton, CA (Hybrid Onsite)
Experience: 2 Years

We are looking for a Junior QA Automation Engineer with hands-on experience testing and automating AI Agents, including Salesforce Agentforce and other generic/LLM-powered agents. The ideal candidate will have a strong understanding of QA automation fundamentals and at least 2+ years of experience working with Agentic AI, LLMs, AI tools, or AI-driven applications.

Key Responsibilities

·         Design, develop, and execute automated test cases for AI Agents and Agentic AI applications.

·         Test Salesforce Agentforce agents and other AI/LLM-based agents for functionality, reliability, and expected behavior.

·         Develop automation frameworks and test scripts for agent workflows, tools, integrations, and end-to-end scenarios.

·         Validate AI agent responses, tool/function calling, workflows, prompts, and expected outcomes.

·         Perform functional, regression, integration, and end-to-end testing of AI-powered applications.

·         Identify and troubleshoot defects related to agent behavior, integrations, workflows, and automation.

·         Work with developers, QA engineers, and product teams to define test strategies and acceptance criteria for AI features.

·         Use modern AI-assisted development and testing tools such as Cursor, Claude, GitHub Copilot, or similar platforms.

·         Create and maintain automated regression suites.

·         Document test results, defects, test scenarios, and automation coverage.

·         Contribute to improving QA processes and automation practices for AI-based applications.

Required Skills

·         2+ years of hands-on experience with Agentic AI / AI Agents / LLM-based applications.

·         Experience testing or automating Salesforce Agentforce or similar AI agent platforms.

·         Experience with QA automation and automated testing frameworks.

·         Understanding of LLMs, prompts, AI agent workflows, tools/function calling, and AI application testing.

·         Strong understanding of software QA fundamentals, including functional, regression, integration, and end-to-end testing.

·         Ability to create test scenarios for non-deterministic AI/LLM-based applications.

·         Good analytical, troubleshooting, and communication skills.