Full Stack Engineer, AI Prototyping

Who we are

SeekWell is the parent company of 1-800 Contacts, Luna, and The Framery. Our goal is to make it simpler, easier, and more accessible for people to get the vision care they need. We maintain the legendary, award-winning culture 1-800 Contacts started almost 30 years ago and continue to develop innovative, pioneering products and businesses that make consumers cheer. We’re owned by KKR – one of the world’s largest and most successful private equity investment companies.

We’ve built an excellent company and changed an industry by putting the customer first, always. The best is yet to come!

Why you want this job

We're building toward a future where every customer interaction with vision care is seamless, informed, and genuinely personal. Our design and product teams are already exploring the systems and experiences that can make that possible, and AI is core to how we're getting there.

The CX Incubator exists to rapidly build and test new concepts for our mobile app before larger investments are made. We're looking for a hands-on Full Stack Engineer focused on AI prototyping who combines strong software engineering, deep frontend experience, strong applied AI experience, and product and design instincts to turn ambitious customer experience ideas into functional, testable prototypes.

You'll work alongside a marketer and designer to take concepts from ideation to realistic, testable simulations and prototypes. You'll also help build and evolve our React/Next.js prototyping platform, which enables non-technical partners to rapidly create and experiment with app experiences.

A key part of this role is determining how AI should be applied to a customer problem—not simply integrating a predefined solution. You'll evaluate different AI models, services, and technical approaches and determine how to apply them to experiences involving conversational AI, content decisioning, recommendations, personalization, generative experiences, voice interactions, and other emerging capabilities.

You'll use AI-native development tools and workflows to move quickly from idea to working simulations and prototypes. This role isn't simply about using AI to code faster; it's about understanding, evaluating, and applying AI technologies, making sound technical decisions, and independently figuring out how to turn loosely defined concepts into working POCs.

The goal is to prove out both the customer experience and the technology behind it—not to build the final production-ready solution.

This is a role for an experienced builder who is comfortable with ambiguity, can independently determine technical approaches, enjoys creating working solutions quickly, and learns through experimentation.

What you’ll do

• Turn ideas, customer problems, and hypotheses into functional, testable prototypes across web and mobile experiences.
• Help build and evolve our React/Next.js prototyping platform, including reusable components and integrations that enable rapid experimentation.
• Evaluate different AI models, services, and technical approaches to determine which are best suited to specific customer problems and experiences.
• Build AI-powered experiences using LLMs, existing AI models and services, APIs, customer and product data, and modern web and mobile technologies.
• Prototype customer experiences involving content and intelligent decisioning, recommendations, personalization, generative content, conversational AI, voice, retrieval/grounding, agents, and other emerging AI capabilities.
• Independently determine the technical approach needed to take loosely defined AI-powered concepts from idea to a functional, testable POC.
• Rapidly test different technical approaches and evaluate tradeoffs including experience quality, reliability, latency, complexity, and cost.
• Recognize when AI is—and isn't—the right solution and combine AI capabilities with traditional software approaches when appropriate.
• Create realistic customer simulations that can be tested with internal and external audiences.
• Explore how to ground, guide, and evaluate AI experiences using customer profile data, customer context, and human-defined guardrails.
• Connect prototypes to content libraries, AI SDKs, APIs, data sources, and staging systems.
• Explore AI-forward design systems and guardrails that help generated experiences and agents stay within defined UX, brand, content, and interaction guidelines.
• Use AI-native development workflows with tools like Cursor, Claude, Copilot, and similar technologies.
• Help define practical guardrails for safe, reliable, and brand-appropriate customer-facing AI experiences.
• Use feedback from customer and user testing to rapidly iterate on prototypes and explore different approaches.

What you'll need

Strong full-stack software engineering experience with deep frontend expertise using React, Next.js, TypeScript, or similar technologies, along with hands-on experience building backend services, APIs, and integrations.

Strong hands-on experience evaluating, selecting, integrating, and applying existing AI models, services, or approaches within applications, prototypes, or customer-facing experiences.

Experience working with applied AI capabilities such as LLMs, conversational AI, recommendation or decisioning systems, personalization, retrieval/grounding, agents/tool calling, or generative AI.

Demonstrated ability to evaluate different AI approaches for a use case, understand their tradeoffs, and independently determine an appropriate technical approach.

Demonstrated ability to take an ambiguous AI-powered concept from idea to a functional POC or prototype without requiring a predefined technical solution.

Experience integrating APIs, cloud services, data sources, and external systems.

Familiarity with evaluating AI experiences for factors such as quality, reliability, latency, cost, and customer experience.

Familiarity with AI-native development tools such as Cursor, Claude, Copilot, or similar technologies.

Strong product and design instincts and an appreciation for great customer experiences.

Comfort with ambiguity, rapid experimentation, and building enough to test and learn without over-engineering.

Experience incorporating user or customer feedback into prototypes and iterating based on what you learn.

Examples of AI-powered applications, prototypes, or customer experiences you've personally built and the technical decisions you made while building them.

Experience with React Native, native iOS development, or other mobile application development is a plus.