Product Designer – Design Systems

📍 Job Overview

Job Title: Product Designer – Design Systems

Company: bareinsights

Location: Los Angeles, California, United States (Remote)

Job Type: FULL_TIME (Contract)

Category: Design Systems, Product Design, AI Design Tools

Date Posted: August 17, 2026

Experience Level: Mid-Level (2-5 years)

Remote Status: Fully Remote (Global)

🚀 Role Summary

• Design Systems Development: Spearhead the creation and evolution of robust, token-based design systems, encompassing design tokens (color, type, spacing, radius) and comprehensive component libraries with variants and states, for AI model training.

• AI Interaction & Evaluation: Actively prompt AI models to generate and refine design work, rigorously evaluate AI outputs against established design system coherence and visual quality standards, and provide structured feedback for model improvement.

• Cross-functional Collaboration (Design/Engineering): Contribute to the implementation of design systems, either through Figma for design track roles or by providing clear specifications for coded component libraries in React for engineering-focused contributions.

• Contractual Flexibility: Engage in a fully remote, async-friendly contract role with quick turnaround expectations, focusing on delivering high-quality design system assets and evaluations.

📝 Enhancement Note: While the title is "Product Designer – Design Systems," the detailed responsibilities and required skills indicate a specialized focus on the creation, implementation, and evaluation of design systems rather than traditional product lifecycle management. The role is heavily weighted towards design system architecture and AI interaction. The "Product Design Track" mentioned is a specific track within this broader design systems focus, emphasizing adherence to existing systems.

📈 Primary Responsibilities

• Architect and build complete design systems within Figma, including meticulously defined design tokens (color ramps, type scales, spacing, radius) and a comprehensive library of components with all necessary variants and states.

• Develop "golden screens" that exclusively utilize components from the established library, serving as benchmarks for AI training and evaluation.

• Prompt AI models to generate and refine design outputs based on specific briefs, managing multiple conversational turns to achieve desired results.

• Continuously evolve the underlying design system by refining color palettes, type hierarchies, spacing rules, radius values, and component treatments based on AI interaction feedback and evaluation.

• Evaluate AI-generated design outputs for adherence to the design system, overall visual quality, and alignment with the initial brief, specifically identifying and flagging deviations.

• Compare AI-generated design variations, select the most effective outputs, and articulate clear rationale and reproduction prompts grounded in expert design judgment.

• Participate in ranking and voting processes to train AI models on discerning cohesive, high-quality design systems and aesthetic principles.

• Collaborate with engineering teams by providing clear specifications for coded component libraries, ensuring seamless implementation of design system principles in React, Storybook, and token pipelines.

📝 Enhancement Note: The responsibilities highlight a dual focus: the direct creation and refinement of design systems and the critical evaluation of AI outputs against these systems. This implies a need for both strong design execution skills and analytical evaluation capabilities.

🎓 Skills & Qualifications

Education: While no specific degree is mandated, a strong foundation in design principles, visual communication, and user interface design is expected, often acquired through formal education in design, HCI, or related fields, or equivalent professional experience.

Experience: Minimum of 3+ years of professional experience specifically in building and owning token-based design systems end-to-end.

Required Skills:

• Design Systems Architecture: Proven ability to build and own token-based design systems from inception to implementation, including color ramps, type scales, spacing, radius tokens, and component libraries with variants and states.

• Figma Proficiency: Expertise in using Figma for design system creation, component authoring, variant management, and creating comprehensive documentation. Experience with Figma variables is a plus.

• Code System Reasoning: Ability to understand and reason about design systems as expressed in code (HTML/CSS/tokens) and identify interface breaks when specifications are not met.

• UI/Product Design Application: Professional experience applying design systems in an in-house team, agency, or design-engineering role, ensuring strict adherence to specifications.

• Attention to Detail: A sharp eye for adherence to design system rules, noticing subtle drifts in corner radius, casing, spacing values, or other specified attributes.

• Structured Communication: Ability to write clear, structured, and specific creative direction, prompts, and rationale grounded in design systems principles.

• AI Interaction: Experience prompting AI models to generate and refine design work across multiple turns.

Preferred Skills:

• React Development: Experience with React for implementing design systems or understanding coded component libraries.

• Storybook v8: Familiarity with Storybook for documenting and showcasing component libraries.

• Style Dictionary: Experience with Style Dictionary for managing design token pipelines.

• CVA (Component Variant Args): Understanding or experience with CVA patterns for managing component variants in code.

• AI Design Tool Proficiency: Familiarity with AI design tools such as Claude, Figma AI, or similar platforms.

• Eagerness for AI Frontier: A strong interest in working at the forefront of AI-assisted design tooling and innovation.

📝 Enhancement Note: The "dealbreakers" clearly emphasize hands-on, end-to-end ownership of design systems, distinguishing this role from those who only consume or maintain existing systems. The "Required" section balances design execution with analytical and communication skills pertinent to AI interaction.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Design System Case Studies: At least three comprehensive case studies showcasing end-to-end design work, with a strong emphasis on the development and application of token-based design systems.

• Token & Component Library Examples: Visual and conceptual examples demonstrating the structure, depth, and implementation of color ramps, type scales, spacing rules, radius tokens, and component variants.

• Figma System Implementation: Demonstrations of design systems built and managed within Figma, illustrating component organization, variant usage, and adherence to system principles.

• Code System Integration (Optional but Recommended): If applicable, examples or descriptions of how design systems were translated into code (e.g., React components, Storybook documentation) to showcase understanding of implementation.

Process Documentation:

• System Evolution Workflow: Illustrate how design systems are iteratively refined, including processes for token updates, component additions/modifications, and feedback incorporation from AI interactions.

• AI Prompting & Evaluation Process: Detail your methodology for prompting AI models for design generation and your systematic approach to evaluating AI outputs against design system specifications and quality metrics.

• Cross-functional Handoffs: Showcase examples of how design system specifications are communicated and handed off to engineering teams for implementation, ensuring clarity and accuracy.

📝 Enhancement Note: For this role, the portfolio is critical. It must explicitly demonstrate the candidate's ability to build and own a design system, not just use one. The evaluation of AI outputs is a unique aspect that should ideally be addressed, perhaps through a hypothetical scenario or by discussing how one would approach such an evaluation.

💵 Compensation & Benefits

Salary Range: $60 – $100 per hour (USD)

Benefits:

• Contractual Engagement: This is a contract/freelance position.

• Fully Remote: Work from anywhere globally, offering maximum flexibility.

• Async-Friendly: Accommodates different time zones and work schedules, emphasizing asynchronous communication for efficiency.

• Direct Impact: Opportunity to work on cutting-edge AI infrastructure and influence the development of AI design tools.

• Flexible Hours: While a 40-hour work week is implied for full-time, the async nature allows for flexible scheduling.

Working Hours: The role is described as fully remote and async-friendly, implying flexibility in daily working hours, though a full-time commitment (approximately 40 hours per week) is expected. The primary hiring timezone is aligned with New York, United States, suggesting coordination around EST/EDT for key meetings or urgent communications.

📝 Enhancement Note: The hourly rate is competitive for specialized design systems and AI-adjacent roles. The primary "benefits" are the flexibility, remote nature, and the unique opportunity to work with AI in design. Visa sponsorship is explicitly not available.

🎯 Team & Company Context

🏢 Company Culture

Industry: AI Infrastructure, Design Technology, Software Development. bareinsights is a seed-stage startup focused on building the foundational data layers for AI design tools.

Company Size: Seed-stage startup. This implies a fast-paced, agile environment with a lean team, high impact potential for each individual, and a culture of rapid iteration and problem-solving.

Founded: Information not provided, but as a seed-stage startup, it's likely a relatively new venture.

Team Structure: The team is likely small, comprising founders, core engineers, and designers. Collaboration will be direct and hands-on, with a flat hierarchy. This role will likely report directly to a founding team member or a lead designer/engineer.

Methodology: The company's methodology will be heavily influenced by AI development cycles and agile design practices. This includes:

• Data-Driven Iteration: Using AI outputs and evaluations to inform design system improvements.

• Rapid Prototyping & Feedback: Quick turnaround times for design tasks and prompt-based AI interactions.

• Systematic Evaluation: Rigorous assessment of AI-generated designs against defined system standards.

• Code-Design Integration: Close collaboration between design and engineering to ensure fidelity in implementation.

Company Website: https://bareinsights.de/

📝 Enhancement Note: As a seed-stage AI startup, expect a culture that values innovation, rapid execution, and a willingness to experiment. The focus on AI infrastructure means the team is likely technically adept and forward-thinking.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned at a mid-level to senior specialist level within the design domain, specifically focusing on design systems. It requires significant hands-on expertise rather than managerial oversight.

Reporting Structure: Likely reports directly to a Head of Design, CTO, or a Founder, given the startup environment and specialized nature of the role.

Operations Impact: The work directly impacts the core product by building the "data layer" that teaches AI models about design. This involves:

• AI Model Training: Providing high-quality, system-adherent design data to train AI.

• Design System Advancement: Evolving the foundational design language for AI design tools.

• Quality Assurance: Ensuring AI outputs meet defined standards of visual coherence and adherence.

Growth Opportunities:

• Deep Specialization: Become an expert in the intersection of design systems and AI, a rapidly growing field.

• Influence Product Direction: Contribute significantly to the core technology and product strategy of an AI startup.

• Skill Expansion: Gain experience in AI prompting, evaluation, and potentially contribute to the engineering implementation of design systems.

• Leadership Potential: As the company grows, there may be opportunities to lead design system initiatives or mentor junior designers.

📝 Enhancement Note: This role offers a unique opportunity to be at the frontier of AI and design. Growth will likely come from deepening expertise in this niche and contributing to the company's foundational technology.

🌐 Work Environment

Office Type: Fully remote. This role offers the flexibility to work from any location globally.

Office Location(s): While the primary hiring timezone is New York, the role is open globally. This necessitates strong asynchronous communication skills and self-discipline.

Workspace Context:

• Remote Collaboration: Expect to use digital collaboration tools extensively, including Figma, Slack, video conferencing, and project management software.

• Async Workflow: A significant portion of work will likely be done independently, with communication asynchronous to accommodate different time zones.

• Focus on Deliverables: The environment is likely results-oriented, with a focus on delivering high-quality design assets and evaluations within quick turnaround times.

Work Schedule: Fully remote and async-friendly, with an approximate 40-hour work week expected. While precise daily hours are flexible, responsiveness during core business hours for the primary timezone (New York) may be beneficial for critical communications.

📝 Enhancement Note: Candidates must be comfortable with a fully remote and async work style, requiring strong self-management and communication skills.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Review of application, resume, and portfolio to assess experience with design systems and AI interaction capabilities.

• Portfolio Deep Dive: A session focused on reviewing your submitted portfolio, discussing specific design system projects, your end-to-end process, and your approach to AI evaluation. Be prepared to articulate your design decisions and system rationale.

• Skills Assessment/Challenge: Potentially a practical exercise or a case study focused on evaluating AI-generated designs or refining specific design system elements. This might involve prompting an AI or analyzing provided outputs.

• Team/Founder Interview: Discussion about your fit with the startup culture, your motivation for working with AI in design, and your understanding of the company's mission.

Portfolio Review Tips:

• Highlight Ownership: Clearly demonstrate instances where you built and owned a design system from scratch. Use case studies to walk through your process, challenges, and solutions.

• Showcase Token Strategy: Detail your approach to defining and implementing design tokens (color, type, spacing, radius). Explain the rationale behind your choices.

• Demonstrate Component Depth: Present examples of complex components with well-defined variants and states, explaining their utility.

• Address AI Interaction: If possible, include a section or discussion on how you've used or would approach using AI for design generation or how you'd evaluate AI outputs against a design system.

• Clarity and Conciseness: Ensure your portfolio is well-organized, easy to navigate, and clearly articulates your contributions and impact.

Challenge Preparation:

• Familiarize Yourself with Design Systems: Review best practices for tokenization, component architecture, and system maintenance.

• Understand AI Design Tools: If you have experience with AI design tools, be ready to discuss it. If not, research current capabilities and limitations.

• Practice Prompt Engineering: Think about how you would prompt an AI to generate specific design elements or systems, and how you would iterate on those prompts.

• Develop an Evaluation Framework: Consider how you would objectively assess AI-generated designs for coherence, quality, and adherence to a specified design system.

📝 Enhancement Note: The interview process will heavily scrutinize the candidate's practical experience with design systems and their ability to critically engage with AI-generated design work. The portfolio is the primary tool for demonstrating this.

🛠 Tools & Technology Stack

Primary Tools:

• Figma: Essential for design system creation, component authoring, and visual design. Experience with Figma variables is highly relevant.

• React: Preferred for implementing coded component libraries, understanding React is crucial for the engineering track and beneficial for design roles to understand implementation.

• Storybook (v8): Used for documenting and showcasing coded component libraries. Familiarity is a strong plus.

• AI Design Tools: Proficiency or familiarity with tools like Claude, Figma AI, or similar is desirable for direct AI interaction.

Analytics & Reporting:

• Design System Metrics: While not explicitly stated, the role implies tracking adherence, consistency, and potentially the efficiency gains from using the design system.

• AI Output Evaluation Metrics: Developing and applying metrics to assess the quality and coherence of AI-generated designs.

CRM & Automation:

• Not Directly Applicable: This role is not customer-facing or sales-operations focused, so CRM tools are not central. The focus is on design and development tools.

• Token Pipeline Tools: Experience with tools like Style Dictionary for managing design token transformations is a plus.

📝 Enhancement Note: The technology stack is heavily weighted towards design and front-end development tools, with a strong emphasis on Figma and an understanding of how design systems translate into code. Familiarity with AI design tools is a key differentiator.

👥 Team Culture & Values

Operations Values:

• Design Excellence: A commitment to creating robust, well-defined, and high-quality design systems.

• Innovation & AI Frontier: Eagerness to explore and contribute to the cutting edge of AI-assisted design.

• Systematic Rigor: A disciplined approach to design system development, adherence, and evaluation.

• Efficiency & Speed: Ability to work effectively in a fast-paced startup environment with quick turnarounds.

• Collaboration: Openness to working closely with engineering and AI teams, providing clear communication and feedback.

Collaboration Style:

• Async-First: While collaboration is key, the async nature requires proactive communication, clear documentation, and well-defined deliverables.

• Direct & Transparent: In a startup, communication is often direct. Expect open feedback and a collaborative problem-solving approach.

• Cross-functional Integration: Close partnership between design and engineering is implied, especially for the engineering track and for ensuring design system fidelity.

📝 Enhancement Note: The company culture likely values technical expertise, a passion for AI, and the ability to thrive in a dynamic, remote startup setting.

⚡ Challenges & Growth Opportunities

Challenges:

• Bridging Design Systems and AI: Effectively translating complex design system principles into prompts and evaluations for AI models.

• Maintaining Coherence at Scale: Ensuring AI outputs remain consistent with the design system as complexity increases.

• Rapid Iteration Cycles: Adapting quickly to evolving AI capabilities and design system requirements.

• Remote Collaboration: Navigating asynchronous communication and maintaining strong team cohesion across different time zones.

• Defining AI Quality Standards: Establishing objective criteria for evaluating the "quality" and "adherence" of AI-generated designs.

Learning & Development Opportunities:

• AI Design Tool Mastery: Becoming highly proficient in using and training AI design tools.

• Advanced Design Systems: Deepening expertise in complex design token strategies, component patterns, and system governance.

• AI Ethics & Bias in Design: Understanding the implications of AI in design creation and evaluation.

• Contribution to Foundational AI: Playing a key role in shaping the core technology of an AI infrastructure startup.

📝 Enhancement Note: This role presents challenges at the forefront of AI and design, offering significant opportunities for specialized growth and impact.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you built a design system from scratch. What were the key decisions you made regarding tokens and components, and why?"

• "How would you prompt an AI to generate a specific UI component (e.g., a card with multiple states) that strictly adheres to a given design system?"

• "Imagine an AI generated a design that slightly deviates from your established spacing rules. How would you evaluate this, and what feedback would you provide?"

• "Walk me through a complex component in your portfolio. How did you define its variants and states?"

• "What are the biggest challenges in ensuring AI-generated designs are consistent with a design system?" Company & Culture Questions:

• "Why are you interested in working at the intersection of design systems and AI infrastructure?"

• "What excites you about bareinsights' mission?"

• "How do you approach working in a fully remote and async environment?"

• "Describe your ideal collaboration with engineers when implementing a design system." Portfolio Presentation Strategy:

• Structure Your Narrative: For each case study, clearly articulate the problem, your role, your process (focusing on design system creation and AI evaluation), the solution, and the impact.

• Quantify Where Possible: Even for design systems, try to quantify benefits like "reduced development time for UI components by X%" or "increased consistency across Y products."

• Demonstrate System Depth: Clearly show your token definitions and component variants. Explain the "why" behind your design choices.

• Address AI Explicitly: If you have AI experience, weave it into your case studies. If not, be prepared to discuss how you would approach AI evaluation or prompting.

• Be Ready for Live Figma/Prompting: Have your Figma files easily accessible and be prepared to discuss them in detail. You might be asked to perform a short task or discuss hypothetical scenarios live.

📝 Enhancement Note: Interviewers will be looking for a deep understanding of design systems, practical experience building them, and a thoughtful approach to evaluating AI outputs. Your ability to articulate your process and rationale is paramount.

📌 Application Steps

To apply for this operations position:

• Submit your application through the provided Ashby link.

• Portfolio Customization: Tailor your portfolio to prominently feature your experience building and owning token-based design systems. Include detailed case studies showcasing your process from concept to implementation, with a strong emphasis on design tokens and component libraries.

• Resume Optimization: Ensure your resume highlights keywords such as "Design Systems," "Figma," "React," "Style Dictionary," "Component Libraries," "Design Tokens," "AI Design," and specific years of experience in building systems end-to-end. Clearly articulate achievements related to system creation and evaluation.

• Interview Preparation: Practice articulating your design system philosophy, your process for prompting and evaluating AI-generated designs, and your experience working in remote, async environments. Prepare specific examples from your portfolio to discuss.

• Company Research: Familiarize yourself with bareinsights' mission and the broader AI infrastructure landscape. Understand how your design system expertise contributes to their goals.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.