AI Product Builder

Nurseio; Arizona; On-site; USD 120,000 - 180,000; Full time

Job summary

Nurseio seeks an AI Product Builder who combines product thinking with hands-on AI development to turn ideas into working software using Claude Code, Codex, or similar tools. This role sits at the intersection of product management, UX, AI-assisted development, and software engineering.

You’ll own problem definition, design experiences, and actually build the product, validating it with stakeholders before handing it to engineering for production deployment.

Qualifications

• Strong product judgment and ownership.
• Experience taking features from idea to implementation.
• Hands-on with AI-assisted development tools.
• Technical fluency across APIs, databases, and architecture.

Responsibilities

• Understand business problems and define the best product solution.
• Design user flows, screens, and interactions.
• Direct AI-assisted development to build working product.
• Test, iterate, and validate product behavior with stakeholders.
• Handoff to engineering with clear, working specs.

Skills

Product ownership instincts

AI-assisted development

UX instincts

Communication with stakeholders

Problem solving

Tools

Claude/Claude Code

OpenAI Codex

Job description

About the Role

Compensation: Competitive; dependent on experience

Reports To: CTO / Product Leadership

Geography: United States

Department: Product / Technology

Employment Type: Full-Time

Compensation: Competitive; dependent on experience

Reports To: CTO / Product Leadership

Geography: United States

We are looking for an AI Product Builder — someone who combines the product thinking of a Product Manager with the hands‑on ability to turn ideas into working software using modern AI development tools.

This is not a traditional Product Manager or Product Owner role, and it is not a traditional Full‑Stack Developer role.

We are looking for someone who can understand a business problem, determine what should be built, design the user experience and workflow, and then use AI-first development tools such as Claude Code, Codex, or similar platforms to actually build it.

The goal isn't to produce a requirements document and hand it to engineering.

The goal is to produce a working product.

You will take an idea from:

Problem → Product Definition → UX → Build → Test → Iterate → Working Product → Engineering Handoff

Once the product works as intended and the experience has been validated, our engineering team will bring it into our production architecture and ensure it conforms to our engineering, security, RBAC, data‑access, scalability, and infrastructure standards.

This role sits directly at the intersection of product management, UX, AI-assisted development, and software engineering.

What You'll Do

Own the Product Problem

You'll work with leadership, users, operations, engineering, and other stakeholders to understand what we're trying to accomplish and determine the best product solution.

You'll be expected to:

• Understand the underlying business or user problem.
• Ask the questions necessary to uncover the actual requirement.
• Challenge assumptions when a simpler or better solution exists.
• Translate ambiguous ideas into clear product functionality.
• Think through edge cases before they become development problems.
• Prioritize simplicity, usability, and business impact.
• Make product decisions instead of waiting for every detail to be specified.

In other words, you should be comfortable hearing:

“Here’s the problem we’re trying to solve.”

…and figuring out most of what comes next.

Design the Experience

You don't need to be a dedicated UX designer, but you need strong product and usability instincts.

You'll determine:

• User flows
• Screens and interfaces
• States and interactions
• Business rules
• Validation
• Error handling
• Edge cases
• Data requirements
• Administrative workflows

You should care about whether something is intuitive, not merely whether it technically works.

Build It

This is what separates this position from a traditional Product Manager.

You will actually build the product you design.

You'll use modern AI-assisted development environments and tools such as:

• Claude / Claude Code
• OpenAI Codex
• Other emerging AI development tools

You aren't expected to manually write every line of code.

You are expected to understand what the AI is building well enough to direct it, troubleshoot it, evaluate its output, and get the application working correctly.

Depending on the project, that may involve:

• Front-end interfaces
• APIs
• Database schemas
• SQL
• Business logic
• Third-party integrations
• LLM integrations
• Internal tools
• Automation
• Agentic workflows
• Mobile or web experiences

AI should dramatically increase your development velocity — but you remain responsible for the result.

Test and Iterate

Getting something to compile isn't the finish line.

You'll use the product yourself, test it with stakeholders and users, identify problems, and continue iterating until it behaves the way the product was intended to behave. And of course, creating and running end-to-end AI tests throughout the product will be a part of the process.

You'll test:

• Primary workflows
• Edge cases
• Error conditions
• Data integrity
• User experience
• Business rules
• Integration behavior
• AI-generated functionality

You own the product until we can say:

“Yes. This is what we wanted to build.”

Hand Off to Engineering

Our Full-Stack Engineers remain responsible for our production engineering standards.

Once you've proven the product and its behavior, you'll work directly with engineering to transition it into the production environment.

Engineering may refactor, replace, or rebuild portions of your implementation to ensure compliance with requirements including:

• Application architecture
• Security standards
• Authentication and authorization
• Role-Based Access Control (RBAC)
• Data isolation and permissions
• Logging and auditing
• Testing standards
• Performance
• Scalability
• Reliability
• Monitoring
• Deployment and infrastructure standards
• Regulatory or compliance requirements

Your prototype isn't throwaway work, however.

The expectation is that it is sufficiently complete and well understood that engineering isn't receiving a concept or a collection of screenshots.

They're receiving a working product whose behavior has already been defined and validated.

What We're Looking For

We're intentionally flexible about someone's traditional career path.

The right person might currently be a:

• Product Manager who became highly technical
• Product Engineer
• Technical Product Manager
• UX/Product Designer who learned to build
• Software Engineer with exceptional product instincts
• Startup founder or early‑stage employee
• No-code/low‑code builder who progressed into AI‑assisted development
• AI‑native developer or product builder

We're much more interested in what you've built and how you think than what your previous title was.

Core Qualifications

You should have:

• Strong product judgment and product ownership instincts.
• Experience taking products or features from idea through implementation.
• Hands‑on experience building software with AI‑assisted development tools.
• Enough technical understanding to work intelligently with databases, APIs, application logic, and modern software architectures.
• Ability to read and understand code even when AI generated most of it.
• Strong debugging and problem‑solving ability.
• Ability to translate business requirements into product behavior.
• Strong UX instincts.
• Comfort working independently with incomplete requirements.
• Ability to communicate effectively with both business stakeholders and software engineers.
• Strong attention to detail.
• A bias toward building, testing, and learning rather than documenting and debating.
  

Technical Fluency

You do not need to be the strongest software engineer on the team.

You do need enough technical fluency to recognize when something doesn't make sense.

You should be comfortable working with concepts such as:

• APIs and REST/JSON
• Relational databases and SQL
• Front‑end and back‑end application concepts
• Authentication and authorization
• Git and source control