Product Designer
New
S
SpateTrend intelligence SaaS
Source API remote eligibility restrictions: Austria, US Central Time (UTC−6) to Central European Time (UTC+1); core collaboration hours 9:00 AM–12:00 PM EasternFull-TimeMiddle
Salary70,000 - 80,000 EUR per year
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Job Details
- Languages
- Strong written communication in English.
- Experience
- 3+ years of product design experience
- Required Skills
- FigmaProduct designData visualizationPrototyping
Requirements
- Have 3+ years of product design experience, ideally owning features end to end in a B2B or SaaS product.
- Show strong product judgment and be able to explain and revise ideas about what to build and why.
- Provide a portfolio demonstrating problem framing, including at least one case study that starts from a fuzzy problem with no specification.
- Have experience designing data-heavy products such as dashboards, analytics, or reporting tools.
- Have worked within or contributed to a design system and understand how components and patterns scale.
- Bring genuine curiosity about AI products, ideally with hands-on exploration.
- Demonstrate strong written communication in English.
- Be fluent in Figma and use AI tools in your everyday workflow.
- Value autonomy and self-direction.
Responsibilities
- Identify user pain points through customer calls, interviews, feedback, and usage data, then frame problems and propose solutions.
- Help determine what to build and why, and stay involved from initial discussions through launch.
- Choose appropriate deliverables for each problem, including written proposals, user flows, prototypes, and Figma specifications.
- Define how AI features work across chat, reports, and inline summaries, including source attribution, loading, uncertainty, and incorrect answers.
- Shape the voice and structure of AI-generated insights.
- Own the design system’s principles and Figma library, and partner with frontend engineers to align it with the React component library.
- Establish data visualization standards and patterns for AI features.
- Co-own product metrics, user feedback tracking, and quality evaluation for LLM features with the frontend lead.
- Define measurable rubrics for evaluating AI answers for users.
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