AI Developer Engineer – MCP & Frontend / Design Systems

We are looking for an AI Developer Engineer to design and implement a coherent AI ecosystem around our existing Design System. You will explore how AI capabilities can be integrated into Design System workflows, documentation, and developer tools, identifying opportunities to improve how developers discover, understand, and consume Design System components and resources using AI.

Main Responsibilities

• Design, develop, and maintain integrations using the Model Context Protocol (MCP).

• Build or integrate MCP servers and tools that expose relevant Design System resources, documentation, components, or development capabilities to AI assistants.

• Develop reusable AI skills, prompt templates, and structured workflows for common development tasks.

• Package AI capabilities into modular, documented, and easy-to-use assets that can be shared across teams.

• Improve developer productivity by reducing repetitive tasks and simplifying access to technical knowledge.

• Create documentation, examples, templates, and guidelines that encourage adoption and gather internal feedback.

• AI & MCP Focus: Strong software engineering background with practical knowledge of the Model Context Protocol (MCP), including building or integrating MCP servers, tools, or clients.

• Frontend & Design Systems Experience: Strong background in frontend development, ideally with experience working closely with or around Design Systems, component libraries, or UI frameworks.

• Seniority & Experience: Middle/Senior level, with approximately 5 years of professional software engineering experience.

• AI Workflows: Experience designing and implementing reusable prompts, AI skills, agent instructions, or AI-powered workflows into software development processes.

• Architecture & Delivery: Ability to package technical capabilities into modular, documented solutions that other developers can easily adopt, backed by solid API integration skills and clean modular design.

• Experience working with AI coding assistants and agent-based development workflows.

• Familiarity with LLM APIs, tool calling, structured outputs, and context management.

• Experience with TypeScript/JavaScript and modern web development ecosystems.

• Experience with developer platforms, CLI tools, internal tooling, or automation.

• Familiarity with design systems, component libraries, UI frameworks, and technical documentation.

• Experience with automated testing, evaluation, and quality assurance for AI-powered solutions.

• Understanding of AI security, permissions, privacy, and governance.