TL;DR

Lead Software Engineer (Quality & AI): Defining and implementing the quality strategy for Salesforce products with an accent on integrating cutting-edge AI technologies and ensuring the highest quality standards for enterprise applications. Focus on leveraging AI/ML to drive acceleration and accuracy in testing, evaluating LLM performance, and providing technical leadership to improve engineering excellence.

Location: Requires onsite presence in San Francisco, California office.

Company

Salesforce is a leading cloud-based software company specializing in customer relationship management (CRM) products.

What you will do

  • Drive innovation and adoption of AI/ML solutions in existing quality workflows, influencing engineering decisions.
  • Stay updated on AI/ML developments, focusing on their practical application and relevance to Salesforce.
  • Provide technical leadership for R&D, focusing on quality validation techniques and improving throughput.
  • Collaborate with data scientists and ML engineers to improve LLM performance based on quality testing.
  • Assess and optimize Large Language Models (LLMs) for quality, accuracy, relevance, and safety across various use cases.
  • Define and implement robust quality strategies for SaaS products with strong AI/ML and LLM integrations.

Requirements

  • 10+ years of experience in software development engineer in test or quality engineering.
  • Proficiency in Java programming languages with hands-on experience in testing frameworks.
  • Strong understanding of AI/ML principles, including model performance optimization, fine-tuning of Small Language Models, and model distillation.
  • Hands-on experience evaluating Large Language Models (LLMs) and familiarity with GPT-like models.
  • Ability to deliver practical solutions for an active user base, ensuring follow-up enhancements.
  • Excellent written and verbal communication skills and a related technical degree.

Nice to have

  • Prior experience in a Data Science, ML Science, or ML Engineering team.
  • Experience with ethical AI practices, evaluating models for interpretability, fairness, and bias.
  • Strong understanding of public cloud infrastructure (AWS/Azure/GCP) and Salesforce certification.

Culture & Benefits

  • Opportunity to drive innovation and positively influence engineering decision-making.
  • Focus on continuous engineering excellence and high business impact.
  • Mentorship opportunities, acting as a resource for engineers advancing to the next level.
  • Collaboration across industries and technology landscapes (CRM, Modern Data Stack, Analytics & BI, AI).
  • Work in a consultative fashion to improve communication, teamwork, and alignment across teams.