AI‑First Development & Automation
· Drive AI‑assisted development workflows using tools like Cursor IDE to accelerate design system engineering.
· Build and maintain automation scripts (TypeScript/Node) for tasks such as code generation, data transformation, CLI tools, and workflow orchestration.
· Create and optimize design‑to‑code automation pipelines using scripts, APIs, and AI agents.
· Conduct critical review and validation of AI‑generated code to detect errors, hallucinations, accessibility issues, or incorrect API usage.
· Develop reusable AI workflows, prompts, structured patterns, and templates for improving team productivity.
Design System Engineering
· Build and extend components using LIT/Web Components and TypeScript, ensuring alignment with system architecture and standards.
· Develop reusable React components, understanding hooks, props, state management, and framework differences (React vs. LIT).
· Apply and maintain design tokens (CSS custom properties), including semantic, primitive, and fallback token strategies.
· Contribute to strengthening design-system‑aligned automation across component creation, documentation, and validation.
Figma API & Design Tool Automation
· Use the Figma REST API for component extraction, style retrieval, asset generation, automation scripts, and integration with engineering workflows.
· Build or extend Figma plugins/widgets using TypeScript + JSX to support design-to-code and component automation workflows.
· Manage API authentication, rate limits, and webhooks to ensure robust integrations.
Accessibility (A11y) Implementation
· Implement accessible UI components with proper ARIA roles, states, keyboard navigation, and screen reader support.
· Ensure all automated and hand‑crafted component work adheres to WCAG 2.1 AA standards.
· Incorporate accessibility checks into AI automation workflows and code review processes.
AI Workflow Governance & Team Enablement
· Develop and maintain team-wide Cursor rules (.cursor/rules) to enforce coding standards, design conventions, and engineering best practices.
· Educate and enable team members on effective prompt engineering, validation steps, and automation usage.
· Proactively identify repetitive workflows and propose automation-first solutions for team-wide efficiency gains.
· Orchestrate multi‑agent AI pipelines, blending human oversight with automated generation and validation steps.
Innovation & Future‑Ready Capabilities
· Explore and contribute to emerging standards such as Model Context Protocol (MCP) and AI‑tooling integrations.
· Experiment with multi‑agent orchestration, chaining AI calls, and building semi-autonomous systems for productivity improvement.
· Continuously research evolving AI tooling, design-engineering automation opportunities, and integration improvements.