Drimva

Later

VP, User Experience

$220K–$275K

Boston, MA +9 · Remote · Director · Full-time · Posted Aug 18, 2026

Location
Boston, MA
Chicago, Illinois, United States
Los Angeles, California, United States
New York, New York, United States
Remote
San Francisco, California, United States
Toronto, Ontario, Canada
Vancouver, British Columbia, Canada
Vancouver, Washington, United States
Boston, MA
Experience
12+ years in product design or UX, including 8+ years leading and growing a design team.

About the job

Leads UX strategy and execution across Later’s product portfolio, managing designers and partnering with product and engineering to deliver cohesive, scalable, AI-enabled experiences.

What you'll do

  • Lead and develop a UX team while setting shared design standards, systems, and processes across products.
  • Contribute hands-on to strategic product work through rapid prototyping, user research, and AI-enabled design workflows.
  • Partner with company leadership, product managers, and engineering to shape product strategy, architecture, and delivery.

What they ask for

  • 12+ years of product design or UX experience, including 8+ years leading and growing a design team.
  • Experience designing coherent experiences across multiple products or teams and building or scaling a design system or shared UX standards.
  • Strong technical fluency and experience partnering with engineering on platform architecture, APIs, data models, frontend frameworks, and implementation tradeoffs.
  • Proficiency with AI-assisted design, prototyping, and development tools to create working or near-working experiences.

Nice to have

  • Experience in B2B SaaS, marketplace, or platform products.
  • Experience in influencer marketing, creator economy, or social/commerce-adjacent spaces.

Pay

$220,000 – $275,000 USD OTE (base + bonus) — total pay

Tools

AI-assisted design tools, APIs, data models, frontend frameworks, design tokens, AI-assisted design-to-code pipelines

AI focus

Build and test agentic UX and AI prototypes; define human-in-the-loop patterns, AI trust mechanisms, and failure states; use generative AI for design exploration, research synthesis, usability analysis, and design-to-development workflows; develop the team’s applied prompt engineering and computational design skills.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 5, 2026 (UTC)