Salesforce
LMTS (Lead Member of Technical Staff)
$172K–$286K
Washington - Seattle +2 · Office Tech-Flexible · Staff · Full-time · Posted Oct 14, 2026
- Location
- Washington - Seattle
California - Palo Alto
California - San Francisco - Experience
- 10+ years of professional software development experience.
- Education
- Bachelor's or Master's degree in Computer Science, Software Engineering, or a related STEM field.
About the job
Leads architecture, development, and delivery of Salesforce’s Page Builder platform, a high-scale web platform for creating and rendering marketing pages.
What you'll do
- Set technical direction and lead end-to-end design, development, deployment, and production ownership of frontend and full-stack capabilities.
- Integrate generative AI services and tools into engineering workflows, and improve platform performance, scalability, accessibility, and reliability.
- Establish engineering quality practices and mentor engineers while collaborating across product, design, and engineering teams.
What they ask for
- 10+ years of professional software development experience focused on large-scale frontend and full-stack web applications.
- Deep expertise in JavaScript, TypeScript, HTML5, CSS3/Sass/Tailwind, modern frontend frameworks, and Node.js.
- Experience architecting enterprise CMS integrations and dynamic rendering pipelines; knowledge of cloud platforms, APIs, security, testing, and deployment practices.
- Demonstrated technical leadership, cross-functional influence, production troubleshooting, and mentoring experience.
Nice to have
- Practical experience integrating generative AI, LLM tools, or multi-agent workflows; experience with internationalization and localization.
- Experience with enterprise design systems or Web Components, WordPress enterprise architectures, PHP, or WCAG-compliant interfaces.
Pay
$172,500 - $260,100 annually (base salary); $207,800 - $285,800 annually (base salary)
Tools
JavaScript/TypeScript, React, HTML5, CSS3, Node.js, WordPress, Contentful, AWS
AI focus
Integrates generative AI services, pipelines, and engineering tools into development workflows; supports AI-first workflow innovation.
Model-written summary · the original posting is authoritative