Software Engineering MTS
Salesforce
About the Role
Salesforce is the #1 AI CRM. We are looking for individuals passionate about bettering business and the world through AI, driving innovation, and upholding Salesforce's core values.
About The Team
The Component Accessibility Team (CAT) focuses on improving software accessibility by enhancing the developer experience. We build AI tools to shift accessibility as far left as possible, enabling developers to write accessible code without needing to be accessibility experts. Our tools include an accessibility agent that provides knowledge, fix tools, and evaluation systems, delivering accessible code suggestions within developers' existing workflows.
Key Responsibilities
- Creating products that increase developer productivity by automating accessibility into the code writing process.
- Guiding the company's web development efforts as the WCAG lead, ensuring compliance with accessibility guidelines and best practices across Salesforce's UI.
- Owning the full detect → diagnose → fix → verify loop for accessibility violations.
- Ensuring AI solutions for accessibility are grounded in WCAG and internal standards, with rigorous evaluation for trustworthiness and performance.
What You'll Build
- Well-evaluated AI fix tools, including a Jest remediation tool, functional-test (ftest) remediation tool, and an accessibility-guide tool.
- The agent's knowledge base, encompassing accessibility (a11y) best practices, remediation patterns, and Salesforce engineering standards.
- The evaluation system, including the eval dataset and reviewer set (Aura + LWC) to prove WCAG criterion compliance.
- Shared platform capabilities for component identification and verification of semantic fixes.
- Automated coverage for challenging WCAG categories, such as reflow (1.4.10) and focus management (2.4.3, 2.4.7).
- Packaging and adoption strategies to integrate the agent into developer surfaces like AI Suite, DX MCP, Cursor, Claude Code, and Vibes, supported by the Iron metrics dashboard.
What You'll Do
- Build and evaluate AI-powered accessibility tools, developing fix tools and agent skills to generate, validate, and repair accessible code across Aura and LWC.
- Design and expand the eval dataset and reviewer set to prove correctness per WCAG criterion with measurable data.
- Treat evaluation as a first-class deliverable, ensuring no AI capability ships without a measured quality bar.
- Ground work in real accessibility standards by encoding WCAG success criteria and Salesforce internal standards into the agent's knowledge.
- Expand per-criterion coverage and grow the reviewer set to bridge the gap between detection and fixing.
- Ship into developer workflows and drive adoption by packaging tools into Claude surfaces and removing friction for automatic accessibility.
- Remediate real Sa11y test failures and feed learnings back into the tools.
Requirements & Tech Stack
- Strong software engineering fundamentals and a track record of shipping.
- Proficiency in JavaScript/TypeScript and modern web development.
- Familiarity with at least one component framework (LWC, Aura, React, Vue, etc.).
- A quality mindset, utilizing tests, metrics, and evaluation to prove functionality.
- Clear written and verbal communication skills.
- Tech Stack: JavaScript, TypeScript, LWC & Aura, Jest, Selenium/functional tests, WCAG 2.2 / ARIA, AI agent & eval tooling (Claude, MCP, Cursor, LangSmith), AI Suite, DX MCP.
Preferred Qualifications
- Hands-on experience with AI/LLM-assisted development (building agents, tools, MCP integrations, prompts, or evals).
- Working knowledge of web accessibility, including WCAG 2.2, ARIA, screen readers, keyboard navigation, focus management, and color contrast.
- Familiarity with the Salesforce UI ecosystem (LWC, Aura, Base Components) and testing frameworks (Jest, Selenium/functional tests).
- Experience with developer-tooling adoption, telemetry, or metrics-driven product work.