Senior Software Development Engineer in Test - AI Tooling & Automation

Salesforce Software Quality Senior Member of Technical Staff (SMTS) Job Category: Software Engineering About Salesforce We're Salesforce, the Customer Company, inspiring the future of business with AI+Data+CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way.

And, we empower you to be a Trailblazer, too - driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good - you've come to the right place. Job Details We are infusing AI into every aspect of our software engineering.

While AI is writing the code, validation is what needs to be done to meet enterprise quality. We are looking for an enthusiastic Senior engineer who follows the AI-first approach to build and maintain validation of the code and ensure it is production-ready for our customers. This individual will work on Product Led Growth within the Self-Service and Growth organization, focused on helping new customers self-service and get started with Salesforce with a prescriptive out-of-the-box experience that shortens time to value across the entire Customer 360 of Marketing, Sales, Service, and Commerce.

The Product Led Growth team is currently focused on exciting initiatives including Onboarding Workflows, Agentic Getting Started, and Slack UI. This engineer should have an AI-first approach and be able to help the team translate from traditional testing to using AI in driving acceleration and accuracy in testing and be a multiplier using AI tools.

Prior experience working with agentic products is a plus. As a quality SMTS, you will play a key role in defining, implementing, and maintaining the quality strategy for Product Led Growth. You will collaborate with cross-functional teams, including product development and AI teams, to ensure that Salesforce's AI-driven solutions meet the highest quality standards for enterprise applications.

Key Responsibilities Drive Innovation & Adoption: Design, build, and maintain scalable, AI-first testing frameworks and automation suites to validate complex PLG workflows and agentic capabilities. Execute Quality Strategies: Translate high-level quality strategies into actionable automation plans, focusing heavily on validating LLM integrations, prompt accuracy, and deterministic system behaviors.

Hands-on Code Quality & White-Boxing: Dig deep into the application code to understand system architecture, identify quality gaps, perform white-box testing, and actively contribute to fixing code and test flakiness. Human-in-the-Loop & Model Evaluation: Implement and support evaluation processes for subjective quality dimensions of our AI features, including response relevance, user safety, and contextual accuracy.

Cross-Functional Collaboration: Partner closely with developers, product managers, and engineers within the PLG ecosystem to ensure quality is integrated early and continuously throughout the agile delivery lifecycle. Required Skills and Qualifications Strong Java Skills: Strong technical fundamentals of Java, particularly in data structures and algorithms.

AI/LLM Validation Mindset: Hands-on experience evaluating Large Language Models (LLMs) for quality response, including familiarity with GPT-like models and AI evaluation frameworks is a big plus. Agile Delivery at Pace: Proven track record of delivering automation solutions in a fast-paced CI/CD environment, supporting rapid deployment schedules without compromising quality.

Collaboration & Communication: Excellent communication skills, with the ability to work cross-functionally with product managers, engineers, AI/ML engineers, and data scientists. Problem-Solving & Analytical Skills: Strong analytical and problem-solving abilities with a focus on identifying quality gaps and driving improvement.

Preferred Qualifications A software engineer with a strong coding background and understanding of delivering software at pace in Agentic PDLC. Strong experience with white-box testing and fixing code is a huge plus. Experience working with public cloud infrastructure (AWS/Azure/GCP) and/or foundational knowledge of the Salesforce platform (Salesforce Certifications are a plus).

Prior experience testing autonomous agents, conversational UIs, or generative AI workflows.

The typical base salary range for this position is $148,500 - $223,900 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $178,900 - $246,000 annually.