Product Designer / UX Engineer (Capital Markets + AI Prototyping)

📍 Job Overview

Job Title: Product Designer / UX Engineer - Capital Markets + AI Prototyping

Company: Mercata

Location: United States (Remote)

Job Type: Full-Time

Category: Product Design / UX Engineering (FinTech/AI)

Date Posted: December 09, 2025

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

Remote Status: Fully Remote

🚀 Role Summary

• Spearhead product design and UX engineering for an AI-native Research OS targeting fundamental investors in capital markets.

• Leverage AI coding tools (e.g., Cursor, Claude Code, Replit, Lovable) for rapid, 0→1 functional prototyping and production-ready feature development.

• Deeply integrate and refine user interaction models for navigating complex, time-aware knowledge graphs and entity relationships.

• Collaborate directly with founders (CEO and CTO) to drive product vision and user-centric workflow design.

• Translate deep understanding of front-office capital markets workflows into elegant, intuitive, and high-velocity user experiences.

📝 Enhancement Note: This role is a unique blend of design and engineering, requiring a candidate who can not only conceptualize but also build functional prototypes using modern AI-assisted coding tools. The emphasis on "front-office capital markets experience" is critical, indicating a need for practical, hands-on understanding of how buy-side analysts operate. The "AI Prototyping" aspect signifies a move beyond traditional design tools towards a more integrated development process.

📈 Primary Responsibilities

• Design and build functional, interactive prototypes of new product features using AI coding tools, focusing on speed and iteration.

• Iterate on and improve Mercata's existing UI/UX to enhance coherence, speed, and alignment with analyst mental models.

• Conduct direct user research and embed with capital markets analysts to gather feedback, validate designs, and drive rapid iteration cycles.

• Develop and refine the core interaction model for navigating Mercata's time-aware knowledge graph, entity relationships, and event data.

• Translate complex analytical workflows and data structures into clear, intuitive, and efficient user interfaces.

• Collaborate closely with engineering teams to ensure seamless transition of prototypes into production-quality code.

• Champion a culture of rapid prototyping, thoughtful workflow design, and relentless simplification within the product team.

• Contribute to defining the product roadmap and strategic direction from a user experience and workflow perspective.

📝 Enhancement Note: The responsibilities highlight a hands-on, builder-mentality. "Functional prototypes at high velocity using AI-assisted coding tools" suggests a departure from traditional UX roles where designers hand off static mockups. This role requires the candidate to be comfortable coding or at least deeply involved in the coding process using these emerging tools.

🎓 Skills & Qualifications

Education:

Experience:

• 2-4 years of direct front-office capital markets experience (e.g., buy-side equity analysis, associate PM, PM team, or building tools specifically for professional investors).

• Proven experience in product design, UX design, or UX engineering roles, with a strong portfolio showcasing complex workflow and data visualization solutions.

Required Skills:

• Deep understanding of fundamental investment analysis workflows, company valuation, thesis development, and operational pressures faced by buy-side analysts.

• Proficiency in leveraging AI-assisted coding tools (e.g., Cursor, Claude Code, Windsurf, Replit, Lovable) for rapid UI prototyping and functional development.

• Strong workflow and interaction design instincts, particularly for data-dense, multi-step research processes.

• Excellent user empathy and ability to translate user needs into elegant, intuitive interface designs.

• Robust problem-solving skills and a commitment to simplifying complex user journeys.

• Exceptional communication and collaboration skills, with a low-ego, high-ownership mindset.

Preferred Skills:

• Experience with knowledge graph visualization and interaction design.

• Familiarity with modern front-end development frameworks and best practices.

• Experience working with AI/ML-driven platforms or data intelligence tools.

• Background in building or improving tools for financial analysts or portfolio managers.

📝 Enhancement Note: The "Must Have" section explicitly calls for "Startup experience," which is a significant qualifier. The requirement for "2-4 years Front-office capital markets experience" is highly specific and crucial for understanding the target user base. The emphasis on AI coding tools like Cursor and Lovable is a key differentiator for this role.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase at least 2-3 detailed case studies demonstrating end-to-end product design and/or UX engineering processes for complex data-driven applications.

• Projects should highlight experience with user research, workflow analysis, interaction design, and functional prototyping.

• For each case study, clearly articulate the problem, your role, the design/engineering process, key decisions, and measurable outcomes or impact.

• Include examples of how you've used prototyping tools (especially AI-assisted ones if possible) to validate concepts or build functional interfaces.

Process Documentation:

• The portfolio should reflect a structured approach to design and development, including:

  • User Empathy & Research: How you understand user needs and workflows.
  • Ideation & Wireframing: Conceptualization and early-stage design.
  • Prototyping: Creating interactive and functional prototypes (demonstrating AI tool usage is a plus).
  • Iteration & Testing: How feedback is incorporated to refine designs.
  • Handoff/Production: Collaboration with engineering for implementation.

• Evidence of refining existing processes or workflows to improve efficiency and user satisfaction.

📝 Enhancement Note: Given the role's emphasis on "building" and "prototyping," the portfolio needs to go beyond static mockups. It should demonstrate the candidate's ability to create functional prototypes, ideally showcasing their experience with the specified AI coding tools. Case studies should clearly map workflows and user journeys.

💵 Compensation & Benefits

Salary Range:

Benefits:

• Comprehensive health, dental, and vision insurance.

• Stock options or equity grants in an early-stage, venture-backed company.

• Generous Paid Time Off (PTO) and company holidays.

• Professional development budget for conferences, courses, and learning resources.

• Remote work stipend for home office setup and connectivity.

Working Hours:

• Full-time, approximately 40 hours per week.

• Flexible working hours are encouraged, with core collaboration times to be agreed upon with the team to accommodate different US time zones.

📝 Enhancement Note: Salary estimation is based on common ranges for experienced product designers in the US tech sector, adjusted upwards for the specialized capital markets domain knowledge and the dual-hatted UX engineering aspect. Equity is a crucial component for early-stage startups like Mercata.

🎯 Team & Company Context

🏢 Company Culture

Industry: Artificial Intelligence (AI) / FinTech (Capital Markets Research)

Company Size: Early-stage Startup (likely <50 employees based on typical venture-backed rounds)

Founded: Early-stage venture-backed company, focused on defining a new category in investment research.

Team Structure:

• Small, agile, and highly collaborative founding team.

• Close working relationship with CEO and CTO is expected for this role.

• Direct embedment with users for rapid feedback loops.

Methodology:

• AI-native approach to data processing and intelligence layering.

• Focus on building a dynamic, temporally-aware knowledge graph.

• Emphasis on speed, iteration, and user-centric development.

• Data-driven decision-making and continuous improvement.

• Pragmatic approach to building from first principles to solve complex problems.

Company Website: https://mercata.com/ (Assumed from company URL)

📝 Enhancement Note: Mercata is positioning itself as a leader in AI-native research for fundamental investors. The culture is likely to be fast-paced, innovative, and focused on solving complex problems with cutting-edge technology. The "early-stage, venture-backed" nature means high ownership, direct impact, and potential for rapid growth.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as a mid-level to senior individual contributor with significant influence. It's a "designer-builder" role, blending core design responsibilities with hands-on engineering for prototyping. The "UX Engineer" title implies a higher technical bar than a traditional Product Designer.

Reporting Structure:

• Will report directly to either the CEO or CTO, working in close partnership with both.

Operations Impact:

• This role has a direct and significant impact on Mercata's core product offering, shaping how fundamental investors interact with AI-driven research.

• Success will be measured by increased user engagement, deeper product usage, and direct positive feedback from target users, ultimately driving adoption and revenue for Mercata.

Growth Opportunities:

• Deep Specialization: Become a leading expert in designing and engineering AI-powered research tools for capital markets.

• Product Leadership: Grow into a Product Lead or Head of Product role as the company scales.

• Technical Mastery: Hone skills in AI-assisted coding, advanced prototyping, and potentially front-end development.

• Strategic Influence: Contribute significantly to company strategy and product vision.

• Equity Growth: Benefit from the potential appreciation of company stock options as Mercata scales.

📝 Enhancement Note: The unique blend of design, engineering, and domain expertise offers a distinct career path. Growth isn't just about managing teams but about becoming a critical technical and strategic asset within an innovative early-stage company.

🌐 Work Environment

Office Type: Fully Remote (Telecommute)

Office Location(s): United States. This implies adherence to US labor laws and potentially requires candidates to be in specific US time zones for collaborative purposes.

Workspace Context:

• A fully remote environment requiring strong self-discipline, communication, and asynchronous collaboration skills.

• Access to cutting-edge AI prototyping tools and potentially cloud-based development environments.

• A culture that values deep work, focused sprints, and efficient communication.

Work Schedule:

• Standard full-time hours (approx. 40/week).

• Flexibility in daily hours is expected, but candidates must be available for critical meetings and collaborative sessions within US time zones, particularly those overlapping with the founding team.

📝 Enhancement Note: The "TELECOMMUTE" location type and "United States" as the derived country strongly indicate a remote-first or remote-friendly policy for candidates located within the US.

📄 Application & Portfolio Review Process

Interview Process:

1. Initial Screening: Review of resume and portfolio to assess experience, skills, and alignment with role requirements (especially capital markets and AI prototyping).

2. Hiring Manager/Founder Call: Discussion with CEO or CTO to delve into experience, motivations, understanding of capital markets, and approach to design/engineering.

3. Portfolio Deep Dive: A dedicated session to walk through selected case studies from the portfolio. This will focus on design process, problem-solving, user empathy, and technical prototyping skills. Expect questions about specific tools used.

4. Design/Engineering Challenge: A practical exercise, potentially involving a short prototyping task using AI tools or a deep dive into a specific workflow problem Mercata faces. This might be a take-home assignment or a live coding session.

5. Team/Culture Fit Interview: Conversation with other team members (if applicable) to assess collaboration style, ownership, and cultural alignment.

6. Final Interview: Wrap-up with founders to discuss role expectations, compensation, and answer any final questions.

Portfolio Review Tips:

• Highlight AI Prototyping: Explicitly showcase projects where you used AI-assisted tools (Cursor, Claude Code, etc.) to build functional prototypes. Explain the benefits and challenges.

• Capital Markets Focus: Choose case studies that best demonstrate your understanding of financial analysis workflows, data density, and the pressures faced by buy-side investors.

• Workflow Clarity: Clearly map out user journeys and workflows. Show how your design simplified complexity or improved efficiency.

• "Show, Don't Just Tell": Whenever possible, provide links to live prototypes or interactive demos. For static case studies, use clear visuals and concise explanations.

• Quantify Impact: Wherever possible, use metrics to demonstrate the success of your designs (e.g., increased user engagement, reduced task completion time, positive user feedback).

• Be Opinionated: Share your strong opinions on design and workflow, backed by your capital markets experience.

Challenge Preparation:

• Tool Familiarity: Practice with Cursor, Replit, or similar AI coding environments. Be ready to demonstrate basic UI construction and interaction logic.

• Workflow Deconstruction: Be prepared to analyze and propose solutions for complex analytical workflows. Think about how data, events, and entities interconnect.

• AI Integration: Consider how AI can genuinely enhance user workflows, not just as a feature, but as a core part of the user experience.

📝 Enhancement Note: The interview process is designed to rigorously test both design sensibility and practical building capabilities, with a strong emphasis on the candidate's specific domain knowledge in capital markets and their comfort with emerging AI prototyping tools.

🛠 Tools & Technology Stack

Primary Tools:

• AI Coding Assistants: Cursor, Claude Code, GitHub Copilot, or similar.

• Prototyping Platforms: Lovable, Replit, Windsurf, or other environments for building functional UI prototypes quickly.

• Design Tools: Figma, Sketch, or similar for conceptualization and wireframing (though less emphasis than prototyping tools).

• Version Control: Git, GitHub/GitLab/Bitbucket for code management.

Analytics & Reporting:

• While not a primary focus for this role, familiarity with product analytics tools (e.g., Mixpanel, Amplitude) to understand user engagement and behavior would be beneficial.

CRM & Automation:

• Not directly applicable to this design/engineering role, but awareness of how user data flows from front-end interactions into backend systems is important.

📝 Enhancement Note: The core technology focus is on AI-assisted coding and rapid prototyping tools. The candidate is expected to be proficient or quickly become proficient with these specific emerging technologies.

👥 Team Culture & Values

Operations Values:

• Ownership: High degree of responsibility for outcomes, from design concept to functional prototype.

• Speed & Iteration: Embracing rapid development cycles and quick feedback loops.

• Simplification: A drive to distill complexity into elegant, user-friendly solutions.

• User-Centricity: Deep empathy for the target user (capital markets analysts) and a commitment to solving their problems.

• Innovation: Embracing new technologies like AI to redefine research workflows.

• Collaboration: Working closely with founders and users to achieve shared goals.

Collaboration Style:

• Close-knit, transparent, and communicative.

• Expect frequent collaboration with CEO and CTO.

• Emphasis on asynchronous communication where appropriate, balanced with synchronous sessions for deep work and critical decision-making.

• Direct access to users for validation and feedback.

📝 Enhancement Note: The values emphasize a proactive, results-oriented approach, common in successful early-stage startups. The "low ego, high ownership" mindset is critical for thriving in this environment.

⚡ Challenges & Growth Opportunities

Challenges:

• Defining a New Category: Being at the forefront of creating a new product category requires navigating ambiguity and establishing best practices.

• Bridging Design & Engineering: Seamlessly transitioning between high-level design thinking and functional code implementation can be demanding.

• Rapid Technological Evolution: Staying ahead of the curve with AI coding and prototyping tools requires continuous learning.

• User Adoption: Educating and convincing traditional capital markets professionals to adopt new AI-driven tools.

• Balancing Speed with Quality: Maintaining high standards while iterating rapidly in a startup environment.

Learning & Development Opportunities:

• AI Tool Mastery: Become an expert in the latest AI-assisted development and prototyping tools.

• Domain Expertise Deepening: Gain unparalleled insight into the future of capital markets research and AI's role in it.

• Product Strategy Influence: Contribute to shaping the strategic direction of an innovative FinTech startup.

• Entrepreneurial Experience: Gain firsthand experience in building a company from its early stages.

• Networking: Build strong relationships with founders, investors, and industry professionals.

📝 Enhancement Note: The challenges are inherent to an early-stage company defining a new market. The growth opportunities are significant for a candidate who thrives in such an environment and is eager to push boundaries.

💡 Interview Preparation

Strategy Questions:

• Capital Markets Workflow Deep Dive: Be prepared to articulate in detail how a buy-side analyst evaluates a company, tracks changes, builds a thesis, and finds alpha. Draw on your personal experience.

• AI Prototyping Approach: Explain your philosophy and practical approach to using AI coding tools for rapid prototyping. What are their strengths and limitations? How do you ensure quality?

• Design Simplification: How would you approach simplifying a complex, data-dense workflow for a busy analyst? Provide examples from your past work or hypothetical scenarios.

• Knowledge Graph Interaction: Discuss your ideas on how users should best navigate and interact with a dynamic, time-aware knowledge graph of companies, people, and events.

Company & Culture Questions:

• Mercata's Vision: What excites you about Mercata's mission and its AI-native approach to research?

• Startup Fit: How do you thrive in a fast-paced, ambiguous startup environment? What are your expectations regarding ownership and responsibility?

• Collaboration: How do you best collaborate with technical founders and embed with users to gather feedback?

Portfolio Presentation Strategy:

• Focus on Process: For each case study, walk through your thought process, the decisions you made, and why.

• Highlight AI Tool Usage: Clearly demonstrate how you used AI tools to build functional prototypes. Show the output and explain the value.

• Quantify Impact: If possible, use metrics to show the results of your work. If not, articulate the anticipated impact and how you would measure it.

• Be Ready to Discuss Trade-offs: Explain any design or technical trade-offs you had to make and why.

• Ask Insightful Questions: Prepare thoughtful questions about Mercata's product, users, and future vision.

📝 Enhancement Note: Preparation should focus on demonstrating a deep understanding of the target user's pain points, a practical command of AI prototyping tools, and a clear vision for how to translate complex data into actionable insights.

📌 Application Steps

To apply for this Product Designer / UX Engineer position:

• Submit your application through the provided Workable link.

• Portfolio Customization: Tailor your portfolio to heavily feature your capital markets experience and any projects involving AI-assisted prototyping or complex data visualization. Prioritize case studies that showcase workflow analysis and functional UI building.

• Resume Optimization: Ensure your resume clearly highlights your front-office capital markets experience, proficiency with AI coding tools (mention specific ones if possible), and any startup experience. Use keywords from the job description.

• Prepare for a Practical Exercise: Be ready for a design or coding challenge that tests your ability to rapidly prototype using AI tools and address a capital markets workflow challenge.

• Research Mercata: Understand their AI-native approach, their target market (fundamental investors), and their unique value proposition. Prepare questions that demonstrate this understanding.

⚠️ 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.

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