Team lead AI Design Engineer

About the Role
Our client is looking for a senior design technology leader who has successfully built and implemented AI-first design and development workflows in a real production environment.
This is not a traditional Head of Design role, nor is the client looking for someone whose AI experience is limited to experimenting with new tools or improving individual designer productivity.
The core challenge is much more ambitious: redesigning how product design and development work together so that teams can move dramatically faster from idea → prototype → validated design → production-ready implementation.
The client has already explored different AI-assisted design approaches and tools. What they need now is someone who has gone beyond experimentation and has actually built systems, workflows, and operating models that work end to end.
You should be equally comfortable discussing design systems, product design workflows, frontend architecture, AI-assisted development, prototyping, and organizational change.
Your mission will be to help the client build an AI-native design organization where AI is embedded into the way products are designed and shipped, not simply added as another productivity tool.
What You'll Do
Define and implement an AI-first design and development workflow across the client's product teams.
Dramatically shorten the path from product idea to prototype, validated design, developer-ready implementation, and where appropriate, production-ready code.
Build workflows that connect design tools, AI systems, design systems, component libraries, and real application code.
Establish practical approaches for AI-assisted ideation, prototyping, UX exploration, UI generation, design-to-code, iteration, and implementation.
Design systems and processes that allow designers and engineers to collaborate effectively in an AI-native environment.
Evaluate and integrate emerging AI design and development tools based on production value rather than hype.
Partner closely with design, product, and engineering leaders to identify bottlenecks and redesign how teams work.
Help establish or evolve design systems that can be reliably translated into real product components.
Create standards and guardrails that allow teams to move faster without sacrificing product quality, consistency, or maintainability.
Coach designers and engineers on AI-native workflows and help drive adoption across teams.
Measure the impact of these workflows on design and development speed, iteration cycles, and product delivery.
What the Client Is Looking For
Proven experience building and implementing AI-first design and development workflows in a real production environment.
Strong understanding of modern product design workflows and how design connects to engineering.
Hands-on experience integrating AI tools into workflows spanning ideation, prototyping, design, and software development.
Strong understanding of design systems, component libraries, and the relationship between design artifacts and production code.
Enough technical depth to work directly with frontend engineers and understand how design systems are implemented in real applications.
Experience turning experimental AI workflows into repeatable systems that other designers and engineers can actually use.
Strong product and systems thinking: you think beyond individual tools and optimize the entire product development workflow.
Ability to distinguish genuinely useful AI capabilities from demos, prototypes, and hype.
Experience driving meaningful workflow or organizational change across design and engineering teams.
Strong written and spoken English.
What the Client Will Care About Most
The client will be particularly interested in concrete examples of systems you have already built.
For example:
What did the design and development workflow look like before you changed it?
What AI tools, infrastructure, design systems, or internal tooling did you introduce?
How did design artifacts connect to real application code?
How broadly was the workflow adopted by designers and engineers?
What parts reached production?
What measurable impact did it have on iteration speed or time from idea to production?
A compelling demo is useful. A workflow that a real team has successfully used to ship production software is much more important.
Nice to Have
Strong frontend engineering background.
Experience as a Design Engineer, Design Technologist, Product Engineer, or similar hybrid design/engineering role.
Experience building internal AI tools, agents, plugins, or automation for designers and developers.
Experience with modern AI coding and prototyping tools.
Experience building token-based or code-connected design systems.
Experience scaling design systems across multiple products or engineering teams.
Experience leading or building AI-native product, design, or engineering teams.
What Success Looks Like
Within this role, success means changing how the client's teams actually build products.
Designers should be able to explore and validate ideas faster. Engineers should receive higher-quality, more implementation-ready outputs. Design systems should connect more reliably to production code. Repetitive handoffs and manual work should decrease significantly.
Most importantly, AI-assisted workflows should become a real, repeatable part of how the organization ships software, not a collection of isolated experiments.
The result should be a measurable reduction in the time required to move from an idea to a high-quality product experience in production.