Software Engineering SMTS (Salesforce AI Quality Engineer)

Salesforce is seeking an experienced Quality Engineer for their Agentforce team within the Digital Success Engineering organization. This role combines traditional software quality engineering with cutting-edge AI testing expertise, focusing on Retrieval-augmented Generation (RAG) and Agentic technologies. The position requires a unique blend of Salesforce platform knowledge and AI/ML testing capabilities.

The Digital Success Engineering team is a diverse group working to build Unified Experiences for Salesforce Trailblazers. As customer zero, they drive innovation by leveraging Salesforce technology to create seamless self-service experiences. The role involves developing comprehensive testing strategies for AI-powered features, including RAG, Agentic workflows, and Large Language Models.

The ideal candidate will have extensive experience in software quality engineering (7+ years), with specific expertise in Salesforce platform (2+ years) and AI/ML testing (3+ years). They should be proficient in programming languages like Python or Java, and have hands-on experience with modern testing frameworks and tools. The role requires both technical expertise and strong collaborative skills to work effectively with cross-functional teams.

Key responsibilities include developing automated testing frameworks, managing test data for AI models, implementing CI/CD pipelines, and ensuring the quality of complex AI-driven features. The position offers the opportunity to work with cutting-edge AI technologies while contributing to Salesforce's mission of helping companies connect with customers in innovative ways.

This role is perfect for someone who combines strong technical skills with a strategic mindset and excellent communication abilities. The successful candidate will play a crucial role in shaping the future of AI-powered customer success tools at Salesforce, working with the latest technologies in AI and quality engineering.