We are seeking an experienced Design System Manager to support the Digital Experience Leads in defining and delivering the roadmaps, ensuring seamless collaboration across teams, and managing key deliverables.
The Design System supports both web and mobile native apps, working closely with web and mobile native teams to ensure consistency across platforms. The design system team is responsible for creating and maintaining the web design system assets, while also designing for both web and app platforms.
This role requires experience with design systems, including tokens, components, patterns, and documentation, as well as familiarity with design operations and tooling. Experience in web design and development processes is also key. The ideal candidate will bring strong organisational skills, excellent communication abilities, and a solid technical understanding of design and development workflows.
Key Responsibilities
Own the product vision of the Design System
Clear positioning: what the DS is for and what it is not
Target users
Metrics: adoption, reuse, contribution rate, reduction of custom UI
Acts the interface between squads and platform
Translate squad needs into platform-level capabilities
Decide what becomes a shared component vs what stays local
Say no a lot, with arguments, not vibes
Manage the backlog like a real product
Prioritize based on impact across squads, not who shouts louder
Balance new components, improvements, tech debt, and adoption work
Build and maintain web design system assets, ensuring quality and usability.
Drive adoption, not just delivery
Track usage and duplication
Push migrations, deprecations, and cleanup
Make it easier to use the DS than to bypass it
Align with product and tech leadership
Sync with Product Directors on roadmap dependencies
Align with Platform and Frontend leads on architecture and constraints
Make tradeoffs explicit and visible
AI integration & tooling
Identify and implement AI-assisted workflows that meaningfully improve the team's output: component documentation generation, accessibility audits, token suggestions, spec-to-code pipelines, and more.
Evaluate AI tools critically separating useful signal from hype — and making adoption decisions based on real quality and speed gains.
Stay ahead of the curve on how Figma, code generation tools, and LLM-based assistants are changing the designer-developer handoff.
Establish guidelines for responsible AI use within the team: what's automated, what still needs human judgment, and why.
Prototype and test new AI-powered workflows before scaling them — treating experimentation as part of the role, not a distraction from it.