About Us

We are a technology services company dedicated to helping organizations build and deploy cutting-edge AI solutions. From generative AI and custom LLM integrations to predictive analytics and intelligent automation, we work across industries to bring real-world AI applications to life. Our projects combine deep technical expertise with hands-on client collaboration to solve high-impact problems.

Job Summary

We are seeking a Lead AI Experience Designer to serve as the founding design hire. You will establish UX/UI practices for Eliza’s client AI solutions — turning powerful AI capabilities into polished, intuitive, client-ready products. This is a strategic, hands-on role for a designer who can move from ambiguous business problems and user research to sharp product direction, tested prototypes, and polished interfaces.

As Eliza’s first dedicated designer, you will shape not only individual products but also how we approach design as a company: our standards, patterns, tools, and approaches. You will partner directly with AI Product Managers, Forward Deployed Engineers, and client stakeholders — advising across multiple engagements while embedding deeply in the highest-priority, experience-intensive work.

Your primary focus will be elevating the end-user experience and interface quality of Eliza’s AI solutions, from early workflows and prototypes through production-ready UI. The right person is AI-native in their practice — using modern AI tools to accelerate research, ideation, prototyping, testing, and production — while bringing strong judgment about where human craft and rigor matter most.

Key Responsibilities

1. Define Design Standards

Establish the principles, standards, and operating rhythm for AI product design at Eliza.

Establish reusable design systems and interaction patterns that enable FDEs to build consistent, production-ready AI experiences across client engagements.

Create practical design playbooks, templates, and review practices that help delivery teams move from discovery to validated, high-quality interfaces faster.

Bring a clear point of view on what great AI product experiences require — and make that point of view practical for product, engineering, and client teams.

2. User Discovery & Product Direction

Lead user discovery, workflow research, concept testing, and usability testing with client stakeholders and end users, using AI-native research tools to accelerate synthesis and insight generation.

Synthesize insights into clear user needs, opportunity areas, journey maps, and product recommendations.

Turn ambiguous business and technical problems into focused product and UX direction.

Help teams distinguish between an impressive AI demo and a useful, trustworthy product experience.

3. Experience & Interface Design

Design end-to-end user experiences for AI-enabled products, from early concepts and workflows to high-fidelity interface design.

Create clear, intuitive interaction patterns for AI products, including moments where users need transparency, control, feedback, or confidence in the system’s output.

Produce the artifacts that move delivery forward: flows, wireframes, prototypes, visual systems, and implementation-ready specifications.

Raise the quality bar for visual and interaction design across priority client engagements.

Set a new bar for what enterprise AI products can feel like: elegant, trustworthy, and unmistakably designed for the people who rely on them.

4. Delivery Partnership

Partner closely with AI Product Managers and Forward Deployed Engineers to keep product, technical, and experience decisions connected throughout delivery.

Partner with FDEs to translate complex AI-system capabilities and constraints into flexible, SDK-informed interface standards that make multimodal, streaming, and real-time experiences predictable and production-ready.

Participate in client-facing working sessions, presenting design rationale and guiding stakeholders through decisions and tradeoffs.

Support iterative development by testing prototypes and in-progress builds, identifying usability issues early, and helping teams make practical improvements.