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EPAM Design Studio in Poland is hiring a Senior / Lead UX/UI Designer for a new client engagement: an AI-native product built end-to-end for a global financial-services client. You will work as an extension of the client’s design team, partnering directly with their Head of Design and a multidisciplinary delivery team to shape a platform that makes complex decisions clear, transparent and human-centered.
This role sits where design systems, code and AI meet. Beyond crafting great experiences, you will help build the bridge between Figma and the codebase, so that both engineers and AI agents consistently follow the design system, design principles and accessibility standards. You bring a pragmatic point of view on where AI accelerates design work and where human judgment must lead.
Please note that the position requires 5 days of on-site office engagement.
- Product UX/UI Design: Design and refine end-to-end experiences for a new product, from concept to production-ready UI, as part of a global design team
- Design System Ownership: Build, evolve and govern a design system in Figma (tokens, components, variants, documentation) and keep it aligned with its coded counterpart in the repository and Storybook
- Figma-to-Code Bridge: Connect Figma and the repository using AI and LLMs (Figma API / MCP, Code Connect, custom tooling) so design decisions flow reliably into code
- AI Guidance Architecture: Structure the context AI needs inside the repository, e.g., Markdown-based guidance files, routing and linkage between components, so AI output follows design principles, design standards, accessibility (WCAG) and front-end conventions
- Human-in-the-Loop Judgment: Define where AI does the heavy lifting and where human review and hands-on craft are required, and set quality gates accordingly
- AI-Native Delivery: Work within an AI-native SDLC alongside engineers, product owners and QA, contributing to agile ceremonies were needed, and shared definitions of done
- Stakeholder Collaboration: Present and articulate design rationale to client stakeholders, gather feedback and iterate quickly
- Prototyping & Validation: Prototype flows and interactions to test ideas with users and stakeholders
- Share learnings across the team and help raise the bar for AI-enabled design workflows
- Experience: 5+ years in UX/UI or product design at senior or lead level, with a portfolio showing complex product work and hands-on design-system contributions
- Design Systems: Proven experience building and scaling design systems in Figma: variables and tokens, component architecture, documentation and governance
- Design to Code: Solid understanding of how a design system lives in a repository (tokens, components, versioning) and hands-on experience with Storybook
- AI in Design Workflows: Proven, hands-on experience connecting AI / LLMs to Figma (API, MCP or plugins) and to the codebase, including building routers, prompts or Markdown-based guidance that keep AI output consistent with the design system
- Standards & Front-End Literacy: Strong command of design principles, accessibility standards (WCAG 2.2) and enough web-coding knowledge (HTML, CSS, component-based frameworks) to work fluently with engineers
- Point of View on AI: A clear, evidence-based perspective on what AI does best in design work and where human intervention remains essential
- Engineering Collaboration: Proven experience working with development teams across the SDLC, ideally in an AI-native SDLC
- Multidisciplinary Teamwork: Comfortable in cross-functional, distributed teams spanning design, engineering, product and QA, including collaboration with US-based colleagues
- Self-Steering: Able to own your workstream, make decisions under ambiguity and deliver in a fast-paced environment. We leave our ego at the door
- English Proficiency: Expert-level written and spoken English, with the ability to clearly articulate complex ideas, design rationale and strategic thinking
- Financial-services domain knowledge (investment, wealth management or fintech products)
- Experience with design-token pipelines (e.g., Tokens Studio, Style Dictionary)
- Hands-on use of AI-assisted coding tools (e.g., Cursor, Windsurf, Claude Code) or prototyping in code
- Client-facing consulting experience