Manager (IC), Product Design - Design Systems

Requirements

• At least 6 years of experience in a Product Design, Systems Design, or Design Engineering role.
• At least 5 years building and scaling multi-level design systems.
• Experience navigating highly regulated, data-heavy, or premium/travel-specific digital ecosystems.
• A strong portfolio demonstrating complex systems problem-solving, UI engineering artifacts, and documentation of automated or dynamic layouts.
• Deep code literacy with the ability to navigate, review, and collaborate within front-end code repositories (e.g. React, HTML/CSS, or token pipelines). Experience leveraging AI-assisted development tools to accelerate table-stakes front-end implementation and prototyping is highly valued.
• Experience utilizing advanced AI tooling or LLM workflows (e.g. Claude, automated code generation) within design or development pipelines.
• At this time, Capital One will not sponsor a new applicant for employment authorization for this position.
• The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pa

Additional Information

Manager (IC), Product Design - Design Systems We are seeking a visionary, tech-forward Product Designer, Design Systems to join our Premium Products and Travel Design team. In this role, you will sit at the intersection of advanced system logic, human-centered design, and front-end engineering. You will operate across portfolios, ensuring our premium digital experiences scale seamlessly while maintaining an uncompromising standard of craft. This is not a traditional Figma-only system role: you will own the end-to-end lifecycle of our component architecture-from initial tokenization in Figma to production-ready code. Furthermore, you will future-proof our design ecosystem. As generative AI and tools redefine interface production, you will transition from a traditional asset creator to an experience auditor, logic planner, and automation coach. You will design the rules, data schemas, and guardrails that govern AI-native environments, ensuring that automated outputs never compromise a cohesive customer journey. Key Responsibilities & Competencies End-to-End Component Ownership: Build, govern, and maintain scalable component libraries. Act as the long-term guardian of components across design files and code repositories by collaborating directly inside the repo with engineering, reviewing code for design parity, and shipping foundational front-end updates when needed. AI & Automated Interface Governance: Establish the system logic, prompt criteria, and UX frameworks necessary to guide AI-generated patterns. Serve as an experience auditor to prevent fragmented user experiences. Systems Thinking & Data Architecture: Navigate complex tech ecosystems, mapping disparate data schemas into structurally sound user flows. Design sophisticated component interactions optimized for both human users and automated AI agents. Cross-Functional Pod Leadership: Act as the core design catalyst within a dedicated cross-functional pod, serving as the technical peer to engineers. Partner seamlessly with Enterprise Design Systems teams to ensure local Premium systems align or intentionally deviate from macro enterprise standards. Quality Assurance & Experience Metrics: Perform rigorous heuristic evaluations of live experiences. Establish clear frameworks and UX metrics to measure the health, adoption, and end-to-end coherence of system journeys. Design Community Leadership & Practice Maturation: Act as a player/coach and technical mentor for the design team. Lead workshops, facilitate onboarding for new product teams, and coach traditional product designers on scaling their systemic thinking and technical fluency. Champion a robust contribution governance model that empowers other designers to co-create and evolve the system without breaking core integrity. Expected Outputs Production-Ready Component Repositories & Token Pipelines: Living, accessible UI component libraries and design token schemas implemented seamlessly across design files and front-end repositories. AI-Native Design Guardrails: Playbooks, logic schemas, and constraint models that dictate how automated tooling generates layouts without losing brand integrity. End-to-End Journey Optimization: Thorough gap analyses and "North Star" servicing roadmaps that align technical scalability with premium user experiences. Systemic Documentation: High-fidelity spec sheets, accessibility (A11y) mapping, and clear documentation governing the interaction between human intent and automated agent execution. Contribution Frameworks & Enablement Programs: Scalable onboarding materials, contribution guardrails, and educational workshops that upskill the design team on utilizing advanced tokens, code parity workflows, and AI-assisted design tooling.

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