Senior AI-Native Product Designer

📍 Job Overview

Job Title: Senior AI-Native Product Designer

Company: Ōura

Location: San Francisco, California, United States

Job Type: Full-Time

Category: Product Design / AI / Health Technology

Date Posted: April 03, 2026

Experience Level: 5+ Years

Remote Status: Hybrid

🚀 Role Summary

• Architect foundational systems and agentic workflows for intelligent, context-aware user experiences, focusing on AI-native design principles.

• Define and design probabilistic user experiences, managing AI uncertainty, hallucinations, and user trust, particularly within sensitive health data contexts.

• Collaborate closely with Data Scientists and ML Engineers to shape AI model outputs into meaningful, actionable, and user-centric insights, influencing ontologies, logic gates, and feedback loops.

• Develop high-fidelity, functional prototypes using modern tools like React, LLM APIs, and Vercel AI SDK to validate complex AI logic and contextual triggers before production.

• Lead the creation of Generative UI frameworks and contextual tokens that enable personalized, on-the-fly experience assembly based on individual user data.

📝 Enhancement Note: This role is positioned as a "Senior AI-Native Product Designer" within the "Platform Team" at Ōura, indicating a strategic focus on building the core infrastructure for AI-driven product experiences rather than just designing individual features. The emphasis on "AI-Native" and "Platform" suggests a need for deep understanding of AI capabilities and constraints, system-level design thinking, and the ability to create scalable design patterns for intelligent systems. The mention of "HealthOS" as a mission statement implies a focus on a comprehensive health data platform.

📈 Primary Responsibilities

• Design agentic workflows that anticipate user needs and provide "one-step-ahead" utility through ambient and screenless interactions, moving beyond traditional chat-box paradigms.

• Define interaction patterns for probabilistic user experiences, including how the system communicates confidence levels, handles AI hallucinations, and maintains user trust with sensitive health data.

• Bridge the gap between design and data science by shaping model outputs into human-centric experiences, defining ontologies, logic gates, and feedback loops for AI learning.

• Create high-fidelity, functional prototypes using React, LLM APIs, and Vercel AI SDK to test complex AI logic, contextual triggers, and agentic behaviors.

• Lead the development of Generative UI frameworks and contextual tokens that allow the platform to dynamically assemble personalized experiences based on a user's unique "Healthspan" data.

• Champion "Calm Intelligence" by filtering raw health data noise into calm, actionable, and timely insights, preventing cognitive overload for the user.

• Navigate deep-dive technical discussions with backend and ML engineers, speaking the language of APIs, RAG, and latent space to align stakeholders on a technical vision.

• Contribute to the definition and refinement of the AI platform's design system and component library, ensuring consistency and scalability across AI-driven features.

📝 Enhancement Note: The responsibilities highlight a unique blend of traditional product design skills with advanced AI and technical expertise. The emphasis on "agentic workflows," "probabilistic UX," and "generative systems" indicates a forward-thinking role that requires hands-on prototyping and a deep understanding of AI's potential and limitations in creating user-centric experiences, especially within the health domain. The expectation to "speak the language of APIs, RAG, and latent space" underscores the technical depth required.

🎓 Skills & Qualifications

Education: While not explicitly stated, a Bachelor's or Master's degree in Design, Human-Computer Interaction, Computer Science, or a related field is typically expected for senior-level roles with a strong technical component.

Experience: 5+ years of proven track record in Senior or Staff Product Design roles, with a significant focus on AI/ML-driven environments.

Required Skills:

• AI-Native Design Mindset: Deep understanding of AI as a design material; familiarity with LLMs, embedding models, and predictive analytics capabilities and constraints.

• Prototyping & Development: Proficiency in React/Typescript or native code, with the ability to build high-fidelity, functional prototypes that interact with real data models to test agentic behaviors.

• Modern Design Tooling: Expert-level proficiency in Figma, including advanced features like Variables and Config, combined with experience in AI-accelerated workflows (e.g., Cursor, v0, prompt engineering for UI generation, automated documentation).

• Systems & Logic Literacy: Deep understanding of translating design logic into backend architecture, experience with "headless" systems, and designing for multi-modal inputs (voice, haptic, ambient).

• Technical Communication: Ability to navigate deep-dive sessions with backend and ML engineers, understanding APIs, RAG (Retrieval-Augmented Generation), and latent space concepts.

• Portfolio of Intelligent Systems: A strong portfolio showcasing experience with high-complexity data and AI-driven interactions, demonstrating how AI's "black box" was managed to create transparent, user-centric experiences.

• User Experience Design: Proven ability to design intuitive, user-friendly interfaces and workflows, particularly for complex or data-intensive applications.

Preferred Skills:

• Experience designing for health or wellness technology platforms.

• Familiarity with data science concepts and methodologies.

• Experience with Vercel AI SDK or similar frameworks for AI-powered applications.

• Understanding of calm technology principles.

• Experience with ontologies, logic gates, and feedback loop design for AI systems.

📝 Enhancement Note: The requirement for "Code-As-Craft" and the specific mention of React/Typescript and functional prototyping with LLM APIs indicate that this is not a purely conceptual design role. Candidates are expected to have hands-on technical skills to bring AI-driven concepts to life and validate them. The portfolio requirement is specifically geared towards demonstrating experience with complex data and AI, emphasizing the ability to manage the inherent uncertainties of AI.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• AI-Driven Interaction Case Studies: Showcase projects where you designed and implemented complex AI-driven interactions, focusing on how you managed uncertainty, user trust, and data sensitivity.

• System Architecture & Design: Provide examples of how you designed scalable systems and frameworks (e.g., Generative UI, contextual tokens) that enable personalized experiences at scale.

• Functional Prototyping Examples: Include demonstrations or detailed descriptions of functional prototypes built using code (React/Typescript) and AI APIs, illustrating agentic behaviors and contextual triggers.

• Cross-Functional Collaboration Evidence: Illustrate instances where you collaborated effectively with Data Scientists and ML Engineers, demonstrating your ability to translate technical outputs into user-centric designs.

• UI/UX for Complex Data: Present designs that effectively distill complex data (e.g., health metrics) into calm, actionable insights for users.

Process Documentation:

• Workflow Design & Optimization: Document the process of architecting agentic workflows and probabilistic UX, including user research, problem definition, and iterative design.

• AI Integration & Testing: Detail methodologies used for integrating AI models into the design and development process, including prototyping, testing for hallucinations, and defining feedback loops.

• Scalable Design System Development: Show evidence of creating or contributing to design systems, component libraries, and frameworks that support AI-powered features and ensure consistency across the platform.

• Cross-Disciplinary Collaboration Frameworks: Outline best practices and frameworks for effective collaboration between design, data science, and engineering teams on AI initiatives.

📝 Enhancement Note: The portfolio requirements are highly specific to the AI-native nature of this role. It's not just about visual design but about demonstrating the ability to design and prototype complex, AI-driven systems. Candidates need to showcase their technical prototyping skills and their ability to manage the unique challenges of designing with AI, particularly in a sensitive domain like health.

💵 Compensation & Benefits

Salary Range: $172,000 - $203,000 USD per year.

• This range is based on Ōura's "Region 1" market-based compensation approach for US locations, reflecting the cost of labor index for the San Francisco area.

Benefits:

• Competitive salary and equity packages

• Comprehensive health, dental, and vision insurance

• Mental health resources

• An Ōura Ring of your own, plus employee discounts for friends & family

• Generous Paid Time Off (PTO): 20 days annually

• 13 Paid Holidays

• 8 days of flexible wellness time off

• Paid sick leave

• Paid parental leave

Working Hours: The job description implies a standard full-time work schedule, likely around 40 hours per week, with flexibility expected for a hybrid-remote role.

📝 Enhancement Note: The provided salary range is specific to "Region 1" US locations, and the San Francisco location falls within this tier. The benefits package is robust, highlighting a strong emphasis on employee well-being, including unique perks like an Oura Ring and flexible wellness time off. The disclaimer about salary being determined by multiple factors is standard but important to note.

🎯 Team & Company Context

🏢 Company Culture

Industry: Health Technology / Wearable Technology / Software Platforms

Company Size: Ōura is a growing company, though the exact size isn't specified in the provided data, it's implied to be substantial enough to have dedicated platform teams and a global reach. The LinkedIn data would typically provide a range (e.g., 201-500 employees or 501-1000 employees).

Founded: Ōura was founded in 2013, indicating a company with established market presence and experience in the wearable health technology sector.

Team Structure:

• This role is part of the "Platform Team" at HealthOS, which is Ōura's technology division. This suggests a focus on building core infrastructure and enabling technologies rather than direct consumer-facing product features in isolation.

• The team likely comprises product designers, data scientists, machine learning engineers, backend engineers, and product managers, working collaboratively to develop and scale AI-driven capabilities.

Methodology:

• Data-Driven Insights: The company's mission revolves around leveraging data (from the Oura Ring) to provide insights into readiness, activity, and sleep. This implies a strong reliance on data analysis and interpretation.

• Calm Technology Principles: A core philosophy is to create technology that is quiet and doesn't demand attention, returning it to the user. This guides design decisions towards subtle, ambient, and context-aware interactions.

• AI-First Approach: The role explicitly calls for an "AI-Native" mindset, indicating that AI capabilities are central to the platform's development and user experience strategy.

• Iterative Prototyping: The requirement for functional prototyping using modern tools suggests an iterative development process where concepts are quickly built and tested.

Company Website: ouraring.com

📝 Enhancement Note: The company culture emphasizes empowering individuals through health insights, driven by data and advanced technology. The "AI-Native" and "Platform Team" context suggests a highly technical and forward-thinking environment focused on building the future of AI-driven health technology. The "Calm Technology" philosophy is a key differentiator that shapes the user experience.

📈 Career & Growth Analysis

Operations Career Level: This role is designated as "Senior," implying a high level of autonomy, expertise, and the ability to influence product strategy. It sits at the intersection of Product Design, AI, and Platform Engineering, offering a unique career path.

Reporting Structure: The Senior AI-Native Product Designer will likely report to a Design Lead or Head of Product Design within the Platform Team. They will collaborate closely with Data Scientists, ML Engineers, and Product Managers.

Operations Impact: The role has a significant impact on the core AI capabilities of Ōura's platform. By architecting foundational systems and intelligent workflows, the designer directly influences how users understand and interact with their health data, shaping the future of Ōura's AI-driven features and overall product strategy.

Growth Opportunities:

• Technical Specialization: Deepen expertise in AI-native design, generative AI, agentic systems, and calm technology, becoming a thought leader in this emerging field.

• Platform Leadership: Grow into a Staff or Principal Designer role, leading the design vision for critical platform initiatives and mentoring other designers.

• Cross-Functional Mastery: Expand influence by mastering collaboration with Data Science and Engineering teams, potentially leading to roles with broader technical scope.

• Product Strategy Influence: Contribute significantly to the strategic direction of Ōura's AI product roadmap and the evolution of its health technology platform.

📝 Enhancement Note: This Senior role offers a unique opportunity to shape the foundational AI design principles for a leading health tech company. Growth potential lies in specialization within AI design, leadership within platform teams, and significant influence on product strategy.

🌐 Work Environment

Office Type: Hybrid-remote role, requiring at least half-time presence in the San Francisco offices. This suggests a dynamic work environment that balances remote flexibility with in-person collaboration and innovation.

Office Location(s): San Francisco, California, United States.

Workspace Context:

• Collaborative Environment: The hybrid model encourages in-person collaboration for brainstorming, deep-dive sessions, and team building, while remote work allows for focused individual work.

• Technology-Rich: As a tech company, expect access to cutting-edge tools and infrastructure necessary for AI development and design, including high-performance computing and advanced software.

• Cross-Functional Interaction: The role necessitates close interaction with engineering and data science teams, fostering a highly collaborative and interdisciplinary workspace.

Work Schedule: Standard full-time hours are expected, with flexibility inherent in the hybrid model. The emphasis on "Calm Intelligence" suggests a culture that respects focused work time and avoids unnecessary interruptions.

📝 Enhancement Note: The hybrid-remote aspect is a key feature, indicating a modern work approach that values both flexibility and in-person synergy. The San Francisco office serves as a hub for collaborative design and technical discussions.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter will likely review your application, focusing on your resume and portfolio's alignment with the core requirements (5+ years, AI/ML experience, technical prototyping skills).

• Portfolio Review & Technical Deep Dive: Expect a session where you present your portfolio, specifically highlighting AI-driven design case studies, functional prototypes, and your approach to complex data and probabilistic UX. This will likely involve deep discussions with senior designers and potentially engineering leads about your technical craft and system design thinking.

• Design Challenge/Take-Home Assignment: A practical exercise may be given to assess your ability to apply AI-native design principles to a specific problem, potentially involving prototyping or system design recommendations.

• Cross-Functional Interviews: Interviews with Data Scientists and ML Engineers to assess your ability to collaborate, understand technical constraints, and translate AI outputs into user experiences.

• Hiring Manager/Team Lead Interview: A discussion focused on cultural fit, leadership potential, strategic thinking, and alignment with Ōura's mission and values.

Portfolio Review Tips:

• Highlight AI-Native Solutions: Emphasize projects where you designed for AI capabilities and constraints, showcasing your understanding of LLMs, prompt engineering, and generative systems.

• Showcase Functional Prototypes: Prioritize examples where you built interactive prototypes using code (React/Typescript) and AI APIs to demonstrate dynamic or agentic behaviors.

• Detail Your Process: Clearly articulate your design process, especially how you collaborated with technical teams, managed uncertainty, and translated complex data into user-friendly interfaces.

• Demonstrate Systems Thinking: Include case studies that illustrate your ability to design scalable frameworks, generative UI, and contextual systems.

• Quantify Impact: Where possible, provide metrics or qualitative feedback demonstrating the success and impact of your AI-driven designs.

Challenge Preparation:

• Understand Calm Technology: Be prepared to discuss how you would apply calm technology principles to AI-driven health insights.

• AI Hallucination Mitigation: Think about design strategies for handling AI hallucinations and maintaining user trust, especially with health data.

• Agentic Workflow Design: Prepare to outline how you would design workflows where the system anticipates user needs and acts proactively.

• Technical Acumen: Brush up on concepts like RAG, latent space, and API integrations, as you'll be expected to discuss these with engineers.

📝 Enhancement Note: The interview process heavily emphasizes practical application of AI design principles and technical proficiency. Candidates must be ready to demonstrate their ability to not just conceptualize but also build and validate AI-driven user experiences, with a strong focus on their portfolio as proof of their capabilities.

🛠 Tools & Technology Stack

Primary Tools:

• Design & Prototyping: Figma (Expert-level proficiency, including Variables and Config), potentially other tools like Sketch or Adobe Creative Suite.

• AI-Accelerated Workflows: Cursor (AI-native code editor), v0 (AI for UI generation), prompt engineering tools, automated documentation tools.

• Prototyping & Development: React, Typescript, LLM APIs (e.g., OpenAI, Anthropic), Vercel AI SDK.

• Collaboration & Version Control: Git, GitHub/GitLab/Bitbucket, Jira, Confluence.

Analytics & Reporting: While not explicitly mentioned for the designer, familiarity with how user data is tracked and analyzed to inform AI models and design iterations will be beneficial. Tools like Amplitude, Mixpanel, or internal analytics platforms may be in use.

CRM & Automation: Not directly relevant for this design role, but understanding how user data flows into the platform from various touchpoints is important.

📝 Enhancement Note: The technology stack is cutting-edge, heavily leaning into AI-native development tools and frameworks. Proficiency in React/Typescript and the ability to integrate with LLM APIs are critical, positioning this role at the forefront of AI-powered product development.

👥 Team Culture & Values

Operations Values:

• Own Your Inner Potential: This likely translates to encouraging employees to take ownership of their work, growth, and well-being, aligning with the company's mission.

• Calm Technology: A core value guiding the design of products to be unobtrusive, empowering, and respectful of user attention.

• Data-Driven Decision Making: Emphasizing the use of data and insights to inform product development and strategic choices.

• Innovation & Exploration: Fostering an environment where experimentation with new technologies, particularly AI, is encouraged.

• User-Centricity: A commitment to deeply understanding user needs and translating them into intuitive and effective experiences, even with complex AI systems.

Collaboration Style:

• Cross-Functional Partnership: Strong emphasis on close collaboration between Design, Data Science, and Engineering to co-create AI-powered solutions.

• Technical Dialogue: Expect open and direct communication with engineers and data scientists, where technical feasibility and design innovation are discussed constructively.

• Iterative Feedback Loops: A culture that embraces continuous feedback and iteration on designs and prototypes.

• Knowledge Sharing: Encouragement of sharing learnings and best practices, especially around new AI technologies and design approaches.

📝 Enhancement Note: The team culture appears to be a blend of innovation, technical rigor, and user empathy, guided by the unique philosophy of "Calm Technology." Collaboration is key, especially between design and technical disciplines to navigate the complexities of AI development.

⚡ Challenges & Growth Opportunities

Challenges:

• Designing for Uncertainty: Effectively designing user experiences for probabilistic AI outputs, managing hallucinations, and maintaining user trust in sensitive health contexts.

• Bridging Design & AI/ML: Translating complex AI/ML models and outputs into intuitive, actionable, and "calm" user experiences.

• Rapid Technological Evolution: Staying abreast of the fast-paced advancements in AI and LLMs and integrating them effectively into design strategies.

• Scalability of AI-Native Systems: Architecting foundational design systems and frameworks that can scale intelligent, context-aware experiences across a growing platform.

• Balancing Innovation with User Needs: Ensuring that cutting-edge AI features remain genuinely useful and non-intrusive for users focused on their health.

Learning & Development Opportunities:

• Cutting-Edge AI Design: Deep dive into AI-native design, generative UI, agentic systems, and prompt engineering.

• Advanced Prototyping: Master tools and techniques for building functional AI prototypes with LLM APIs.

• Cross-Disciplinary Expertise: Gain in-depth knowledge of ML concepts, data science methodologies, and software engineering best practices.

• Industry Leadership: Opportunity to become a recognized expert in the emerging field of AI-native product design, particularly in health tech.

• Mentorship: Potential to mentor junior designers and contribute to the growth of the design team's AI capabilities.

📝 Enhancement Note: The challenges are directly tied to the innovative nature of the role, pushing the boundaries of AI in product design. The growth opportunities are significant, offering a chance to develop highly specialized and in-demand skills in a rapidly evolving field.

💡 Interview Preparation

Strategy Questions:

• AI-Native Design Philosophy: "How do you approach designing for AI versus traditional software?" or "Describe your philosophy on 'Calm Technology' and how it applies to AI-driven health insights."

• Handling AI Uncertainty: "Imagine our AI provides a health recommendation with low confidence. How would you design the UI/UX to communicate this uncertainty and maintain user trust?" or "What strategies would you employ to design for potential AI hallucinations in a health context?"

• Agentic Workflow Design: "Walk me through how you would design an agentic workflow for a user aiming to improve their sleep quality, where the system anticipates their needs."

• Technical Collaboration: "Describe a time you had to translate complex technical concepts (like RAG or latent space) for a non-technical audience or collaborate deeply with ML engineers. What was your approach?"

• Generative UI Frameworks: "How would you approach architecting a generative UI framework for personalized health dashboards?"

Company & Culture Questions:

• "What excites you most about Ōura's mission and its application of AI in health?"

• "How do you see your experience with [specific tool/skill] contributing to our Platform Team?"

• "How do you approach integrating new technologies and design paradigms into existing systems?"

Portfolio Presentation Strategy:

• Structure for Impact: Begin with a high-level overview of your role and the project's goals. Then, dive into specific case studies, focusing on AI-native challenges and your unique solutions.

• Demonstrate Technical Craft: For each relevant project, clearly show your functional prototypes, explain the technology stack used (React, LLM APIs, etc.), and how they validated your design hypotheses.

• Narrate the Process: Explain your thought process, research, decision-making, and collaboration with technical teams. Use visuals to illustrate workflows, user journeys, and system architectures.

• Highlight AI Design Considerations: Explicitly call out how you addressed AI-specific challenges like uncertainty, context awareness, and data sensitivity.

• Quantify Outcomes: Whenever possible, present metrics or user feedback that demonstrate the success and impact of your designs.

📝 Enhancement Note: Preparation should focus on demonstrating both deep design thinking and practical technical execution within the AI domain. Candidates need to be ready to articulate their vision for AI-native experiences and prove their ability to build them, referencing their portfolio as concrete evidence.

📌 Application Steps

To apply for this Senior AI-Native Product Designer position at Ōura:

• Submit your application through the provided Greenhouse link on the Ōura Careers page.

• Curate Your Portfolio: Select 2-3 of your strongest projects that best showcase your experience in AI-driven design, technical prototyping (React/Typescript, LLM APIs), and system thinking. Ensure these projects highlight your ability to handle complex data and design for uncertainty.

• Tailor Your Resume: Emphasize keywords from the job description, such as "AI-Native," "Product Design," "React," "Typescript," "LLM APIs," "Generative UI," "Probabilistic UX," "Agentic workflows," and your years of experience in senior/staff roles. Clearly list your proficiency with Figma and any AI-accelerated design tools.

• Prepare Your Portfolio Presentation: Practice walking through your selected projects, focusing on your process, technical contributions, and the unique challenges of AI design. Be ready to discuss your functional prototypes and how they informed your design decisions.

• Research Ōura and HealthOS: Understand their mission, products (Oura Ring), "Calm Technology" philosophy, and their strategic direction in AI and health technology. This will help you articulate your interest and cultural fit during interviews.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and industry-standard assumptions. All details should be verified directly with the hiring organization, Ōura, before making application decisions. Beware of potential scams; official communication will come through official Ōura channels.