AI-Native UI/UX Designer
Listed on 2026-10-20
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Software Development
Front End Developer
MUST Company
· Bangladesh, Angola, Cambodia, Botswana, Chile, Ethiopia, India, Indonesia, Pakistan, Kenya, Nigeria, Vietnam, Philippines, South Africa, Nepal, Ukraine, Poland, Romania, Bulgaria, Moldova, Serbia, Georgia, Armenia, Albania, North Macedonia, Bosnia and Herzegovina
AI can now draw a screen in seconds, so anyone can produce a nice-looking screen. What AI can't do is decide which problem is worth solving, notice when a flow is confusing real users, or make a product feel unique. That is the designer we want.
We don't want someone who only polishes screens. You'll look for the real problems in our products, design the fix with AI as your production tool, deliver on time, and show that the change made the product better. We think of design the way Apple does: as a way to solve real problems, not decoration.
About usMUST Company is based in South Korea. We build AI products, Global MPC (our blockchain and crypto project covering crypto mining, digital-asset trading and blockchain products), and Match Hire, the hiring platform this job is posted on. Our team works remotely across Asia, Africa and Europe.
How we workEveryone here owns their area and answers for the results. You don't wait for a brief. If you see something broken, raise it, design the fix and push it through. You'll work directly with the founders and product leads, so decisions happen quickly. We judge work by what changed for users, not by hours online or the number of screens delivered.
Whatyou'll do
- Find UX problems before anyone asks: review real user behaviour, session recordings, support questions and drop-off points across Match Hire, Global MPC products and our internal AI tools.
- Turn each problem into a short brief covering who it affects, what it costs, what you'll change, and how you'll know it worked.
- Use AI tools (Claude, Midjourney, Figma AI, v0, Lovable and similar) to explore many directions fast, then use your own judgement to pick and refine the right one.
- Design complete flows, not just the ideal path: empty, loading, error, mobile and edge-case states.
- Design AI-native experiences people can trust, such as agent progress, approvals, confidence, review and human control.
- Keep a design system and brand language that stops our products from looking like generic AI-generated UI.
- Work with engineers through to release and check that what ships matches what you designed.
- Deliver on the dates you commit to, and say early if a date is at risk.
- After release, measure the result (completion, drop-off, time to finish a task, support volume) and report it in a few lines.
- Month 1:
Learn our products, talk to users and the team, and deliver the top 5 UX problems ranked by impact, with evidence. - Month 2:
Ship the redesign of the most important problem, on the date you committed to. - Month 3:
Show a measured before/after result, and set up a reusable component and pattern library the team actually uses.
What you'll need
- 1+ year designing digital products (web or mobile) that real users use
- A portfolio that shows the problem, your decisions, what shipped and what changed. Polished screens alone aren't enough.
- Strong UX fundamentals: user research, information architecture, interaction design, usability testing, responsive and mobile design
- Strong visual craft: typography, layout, colour and states. Your work should look like yours and not like a template.
- You use AI design and prototyping tools every day, and you can explain where they help and where you override them
- Fluent in Figma, including components, auto-layout and prototyping
- A track record of delivering on time, and of finding and raising problems nobody assigned to you
- Clear written English, and comfort working remotely across time zones
- Basic HTML/CSS or experience prototyping with AI coding tools
- Experience with analytics or behaviour tools (Clarity, Post Hog, Hotjar, Mixpanel)
- A design system you built that other people adopted
- A design decision that turned out wrong, and what you learned from it
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