Senior Design Engineer/ AI-Native Designer

Design with AI. Build in code. Shape AI-powered products.

Star is looking to connect with Senior Design Engineers who have made AI a native part of how they work. We are not looking for designers who occasionally try a generative tool. We are looking for designers who go from idea to working, testable product in code, using an AI setup they have built and refined themselves, and who know how to design products where AI is part of the experience.

AI is fundamentally changing how we design and build products at Star, from the first concept to delivery. Our work spans digital products, automotive and mobility, health tech and emerging platforms for globally recognized brands. We are looking for designers who already work this way and can bring that practice into our projects and to our clients.

This is a contract-based, remote opportunity. Selected designers become part of Star's curated freelance network and may be invited to collaborate on projects that match their expertise, interests and availability.

What you'll do

Design and prototype in code

• Turn concepts into working, code-based prototypes (HTML/CSS, React, TypeScript) in hours or days instead of weeks, using Claude Code as your primary tool (or GitHub Copilot in Microsoft-based client environments);
• Explore several solution directions in parallel and validate them early with real interaction, real data and real users;
• Bridge Figma and code: map components to code components and design tokens to CSS/Tailwind, and keep both in sync;
• Hand working prototypes to Design Researchers for testing, or run quick tests yourself on smaller projects;

Build and maintain the AI harness for design work

• Set up and maintain project context for Claude Code or GitHub Copilot (e.g. CLAUDE.md, rules, conventions, design system references);
• Write and refine reusable skills, prompts and workflows for recurring design tasks;
• Connect tools through MCP (e.g. Figma, repositories, documentation) so AI works with real project context;

Design AI-powered products

• Design assistants, copilots and agentic experiences that people can direct, understand and trust;
• Define interaction patterns for probabilistic behavior: uncertainty, explainability, error and fallback states, human handover;
• Prototype AI features with real models via LLM APIs, including system prompts, tool use and structured outputs, so the actual behavior can be tested;

Work inside the engineering workflow

• Work in Git as a matter of course: branches, commits, pull requests, reviews;
• Collaborate closely with engineers in shared repositories and review design fidelity directly in the code;

Use AI across the whole design process

• Concept variants, UX copy, documentation, specifications and design QA;
• Judge AI output critically: know where AI speeds things up, where it gets things wrong, and where human craft has to take over;
• Keep AI use transparent and traceable in the project: which steps are AI-supported, how quality is checked, what was learned;

Support clients

• Advise client teams on how to integrate AI-native workflows into their own design practice;

Share what works (approx. 20%)

• Share workflows, skills and learnings with Star's design team, for example through pairing, internal sharing sessions or contributions to shared skill libraries;
• Help other designers set up their own AI-native practice.

What impact you'll make

• Shorten the path from brief to a validated, working experience;
• Raise the quality of design decisions by exploring ideas in real, interactive form instead of static screens;
• Shape AI-powered products that are useful, trustworthy and controllable for the people using them;
• Reduce handoff loss between research, design and engineering because design is delivered in or close to code;
• Help clients and colleagues adopt AI-native ways of working that hold up in real projects.

What we're looking for

Required

• 5+ years of professional experience in Product Design, UX/UI or Interaction Design;
• Daily hands-on use of Claude Code (our default) or GitHub Copilot as a core part of your design workflow;
• Confident use of Git and collaboration in shared repositories;
• Experience setting up and maintaining your own AI harness: context files, rules, reusable skills, MCP connections;
• Ability to build functional prototypes in HTML/CSS, React and TypeScript;
• Ability to integrate LLM APIs into prototypes (e.g. Anthropic or OpenAI API, Vercel AI SDK) and define prompts, tools and structured outputs;
• Proven experience designing AI-powered products: assistants, agentic or LLM-based experiences, including patterns for explainability, uncertainty and failure;
• Strong design craft: interaction design, visual hierarchy, typography, systems thinking;
• Expert proficiency in Figma and a solid understanding of design systems and design tokens;
• Critical judgment of AI output and a responsible approach to confidentiality and client data when using AI tools;
• Confidence in client-facing situations: presenting, advising and making the case for your approach;
• Fluent English and clear communication in senior, multidisciplinary and international teams;
• Based in Europe or working in a European time zone;
• A portfolio that shows how you work, not only the results: e.g. live prototypes, repository links, how you validated ideas, examples of skills or workflows you built;

Nice to have

• Contributions to production frontend code or design systems in code (e.g. component libraries, Storybook, token pipelines);
• Experience running usability and concept tests and translating findings into design decisions;
• Experience planning and conducting broader user research independently (e.g. interviews, contextual inquiry, diary studies);
• Experience enabling other designers or client teams: workshops, pairing, coaching;
• Domain experience in complex fields such as automotive and mobility, health tech or industrial software;
• Experience with advanced prototyping tools (e.g. ProtoPie, Framer).

How our collaboration works

0. Apply by submitting your CV, portfolio and links to prototypes, repositories or AI workflows you have built.
1. Portfolio review. We look for AI-native process, prototypes in code, AI product design experience, design craft and evidence of how you have set up your AI workflow.
2. Expert conversation. If your profile is a strong fit, we'll invite you to meet the team and walk us through your way of working.
3. Practical assessment (if needed). A short brief you solve with your own setup, followed by a walkthrough of your result and your AI workflow.
4. Opportunity matching. Selected candidates may be considered for future programs where their expertise is relevant.
5. Project brief and terms. When a suitable engagement appears, we'll share the project scope, timeline, expected contribution, deliverables and commercial details.
6. Collaboration start. Once there is mutual fit, you join the project team and work alongside Star specialists and client stakeholders.

Engagement note

This position is offered on a contract basis and remotely within European time zones. Scope, timeline, availability, deliverables and commercial terms are agreed per engagement.