Carlos Fumo
Architecting the Future of Enterprise Platforms & Generative AI.
I am a Lead Product Designer with 9+ years of experience transforming dense business logic into highly intuitive, scalable digital products. From automating global workflows at Uber to pioneering early multimodal AI search interfaces at You.com, I specialize in shipping high-impact V1 platforms at extreme velocity.
Core Experience
I architect complex enterprise platforms and pioneering AI interfaces, leveraging over a decade of product design expertise to transform dense business logic into high-velocity digital products.
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Generative AI & Search: Joined the founding team at You.com as the sole Product Designer, delivering the V1 multimodal AI chat interface within an aggressive 30-day timeframe to compete directly with ChatGPT and Perplexity.
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Enterprise Platforms & Efficiency: Spearheaded the end-to-end design strategy at Uber for the global Security Center—shipping from ideation to production in under 90 days—and led design operations to modernize heavy-industry rail logistics for Norfolk Southern Railway.
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Fintech & High-Scale E-commerce: Directed design teams at the Samsung Research Institute to deploy secure PIX instant-payment workflows for Samsung Pay, and engineered an omni-channel marketplace chat platform for B2W that generated $600K in annual operational savings.
Education & Certifications
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Bachelor’s Degree in Graphic Design – Centro Universitário Belas Artes de São Paulo.
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Career Essentials in Generative AI – Microsoft & LinkedIn.
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User Research and Design Graduate Certification – University of Minnesota.
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Specialized Professional Credentials: Visual Elements of UI Design (CalArts), Google Analytics Academy, and Design Thinking (Istituto Europeo di Design).
Technical Toolkit
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Design & System Architecture: Figma, Figma Make, Claude Design, Adobe XD, Sketch, Lottie.
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AI & Agentic Workflows: Conversational Frameworks, Custom Microsoft Copilot Agents, Claude, Generative AI Prompting.
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User Research & Product Analytics: Maze, Hotjar, Google Analytics, Adobe Analytics, User Journey Mapping, Persona Mapping, User Interviews.
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Core Methodologies: Design Systems Governance, DesignOps, Cross-Functional Leadership, Problem Framing, Design Thinking, Agile/Scrum.
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Operations & Collaboration: Miro, FigJam, Jira, Confluence, Asana, ClickUp, Trello, Notion.
Expertise
User Research (Qualitative & Quantitative), User Interviewing, Design Systems, Market & Competitive Analysis, User Journey Mapping, and Agentic AI Interaction Design.
Case Study
Launching the World’s First Multimodal AI Chat
Role: Lead Product Designer (Founding Team) Timeline: 1 Month (Ideation to V1 Launch)
In a race against companies like Perplexity and ChatGPT, the goal was to transform a traditional search engine into a conversational AI platform. The primary hurdle was User Trust and Accuracy—how to provide real-time internet responses with verifiable citations and visual data
The Strategy
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Rapid Prototyping: As the sole designer, I utilized Figma and Miro to map user journeys and iterate on UI components daily to hit the 30-day launch window.
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Multimodal Integration: I designed interfaces that could handle not just text, but visual elements like stock charts and AI-generated images via Stable Diffusion.
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Responsible Design: We prioritized transparency by integrating citations directly into the AI responses to solve the "hallucination" problem inherent in LLMs.
Key Features Designed
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Citations UI: A sleek way for users to verify the source of AI claims without leaving the chat.
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Multimodal Response Cards: Custom modules for real-time data, such as Wikipedia snippets and e-commerce integrations.
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AI Image Generation Hub: A seamless workflow for users to prompt and refine images within the search interface.
The Impact
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First to Market: Successfully launched the first consumer-facing LLM with real-time internet access.
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Scalability: The design architecture supported rapid feature expansion into coding assistance (Stack Overflow) and shopping.
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Foundational Success: This V1 paved the way for You.com to become a major competitor in the generative AI space.
Design Justification (The "Why")
"By focusing on a 'Sidecar' citation model and multimodal cards, we reduced the cognitive load for users transitioning from traditional search to AI-driven conversations. My approach was to prioritize speed-to-market without sacrificing the aesthetic precision required for a Silicon Valley product."
Case Study
Uber Efficiency Platform
Senior Product Designer (Platform Engineering) Timeline: Less than one quarter (Ideation to Production)
Uber’s internal data was siloed and overly complex, making it difficult for leaders from IT to Legal to extract actionable insights quickly. The goal was to build a suite of Efficiency Products that could streamline technical documentation and present critical data in a way that informed high-level decision-making.
The Strategy
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C-Level Alignment: Reported directly to the Global CTO, ensuring the tool met the specific needs of Uber’s top leadership.
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Research-Led Design: Conducted extensive User Interviews, Market and Competitive Analysis, and User Journey Mapping to understand the specific KPIs required by different departments.
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Visual Hierarchy: Focused on "Information Density" vs. "Clarity," using Figma, Miro, and Excalidraw to prototype dashboards that could be scanned in seconds.
Key Solutions Designed
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Executive Dashboards: Created streamlined views of complex infrastructure and security data tailored for decision-makers.
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Technical Documentation Platform: Designed a centralized hub for managing technical docs across all internal areas to reduce information fragmentation.
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Unified Design Language: Adapted diverse data streams into a cohesive visual style to ensure consistency across the Platform Engineering suite.
The Impact
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Reduced "Prompt Paralysis" for Leaders: By simplifying how asset costs were presented, I enabled faster approvals for infrastructure adjustments.
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Streamlined Data Presentation: The project focused on improving how data was presented to Uber’s top decision-makers, directly impacting global efficiency
Design Justification (The "Why")
When dealing with data center assets, every percentage of efficiency translates into millions of dollars. My design goal was to create a 'Financial Health Map' of Uber’s infrastructure. By streamlining the visualization of usage costs, we empowered the CTO and other leaders to make infrastructure decisions based on real-time ROI rather than lagging technical reports.