Staff Product Designer: End-to-End, AI-Driven CRM

Clarify

Seattle (WA)

Hybrid

USD 160,000 - 220,000

Full time

4 days ago
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Benefits offered by this job

Health, dental, vision coverage
401(k) with match
Generous parental leave
Offsite retreats

Job summary

Clarify is hiring a senior staff product designer to own end-to-end design for core areas of our AI-native CRM. You’ll collaborate daily with engineers, prototype rapidly with AI, and build reusable patterns so teams ship consistently.

You’ll shape problems with founders and engineers, ship high-fidelity work quickly, and iterate after launch with data-heavy workflows like records and pipelines.

Qualifications

  • You’ve operated at a staff level, setting design direction.
  • You were an early designer at a B2B SaaS startup and shipped product.
  • You move from problem to high-fidelity quickly and iterate after launch.
  • You have strong interaction design instincts for complex, data-heavy tools.
  • You work hand in hand with engineers to implement your designs.

Responsibilities

  • Own design for a core area end-to-end, from problem framing to shipped UI
  • Partner with engineers daily and ship designs into production weekly
  • Design data-dense workflows — records, tables, pipelines, AI agents and signals
  • Prototype with AI tools and code to test ideas before they hit the roadmap
  • Build patterns and components to enable engineers to ship consistently without a designer in every loop
  • Talk to customers and use feedback to decide what to design next

Skills

Staff-level design
B2B SaaS
Rapid prototyping
Interaction design
Engineer collaboration
AI in design

Tools

React/Next.js

Job description

Clarify is hiring a senior staff product designer to own end-to-end design for core areas of our AI-native CRM. You’ll collaborate daily with engineers, prototype rapidly with AI, and build reusable patterns so teams ship consistently.

You’ll shape problems with founders and engineers, ship high-fidelity work quickly, and iterate after launch with data-heavy workflows like records and pipelines.

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