AI Prototyping Engineer

📍 Job Overview

Job Title: AI Prototyping Engineer

Company: Brady Martz

Location: Sioux Falls, South Dakota, United States

Job Type: Full-Time

Category: Technology / Software Engineering / AI Development

Date Posted: September 17, 2026

Experience Level: Entry-Level (0-2 years)

Remote Status: Fully Remote

🚀 Role Summary

• Drive innovation by rapidly transforming nascent business ideas into tangible, deployable AI-powered prototypes.

• Serve as a critical bridge between business stakeholders and the software development lifecycle, ensuring seamless concept validation and efficient production handoffs.

• Develop and refine advanced AI-driven features, encompassing sophisticated prompt engineering, dynamic agent workflows, and robust API integrations.

• Implement rigorous data privacy and security protocols throughout the prototyping process, ensuring compliance for production readiness.

• Continuously evaluate and integrate emerging AI development tools and techniques to enhance prototyping speed, quality, and overall business value.

📝 Enhancement Note: This role is positioned at the intersection of business ideation, AI development, and software engineering. The emphasis on "prototyping" suggests a focus on rapid iteration, experimentation, and proof-of-concept development rather than full-scale production software engineering. The "AI-enabled development tools" and specific mention of "prompt design" and "agent workflows" indicate a strong focus on generative AI and large language models.

📈 Primary Responsibilities

• Conceptualize and develop working prototypes from early-stage business concepts using AI-enabled development tools and rapid experimentation methodologies.

• Collaborate closely with business users and development teams to clarify project objectives, translate requirements into functional prototypes, and assess concept viability.

• Design, build, and iterate on AI-enabled features, including crafting effective prompts, orchestrating agent workflows, integrating APIs, and establishing metrics for AI output quality and reliability.

• Prepare successful prototypes for seamless transition to production, ensuring clear documentation, version control, and structured code for efficient developer handoff.

• Uphold firm data, privacy, and security best practices throughout the prototyping lifecycle to facilitate secure integration with live firm data and production environments.

• Utilize AI tools as a primary development resource while independently validating and verifying all AI-generated output for accuracy, completeness, and reliability.

• Critically evaluate prototypes to identify limitations, edge cases, and potential risks, making informed decisions on further refinement, production readiness, or discontinuation.

• Proactively research and adopt rapidly evolving AI development tools and techniques to improve prototyping efficiency, output quality, and business impact.

📝 Enhancement Note: The responsibilities highlight a hands-on role focused on building and testing. The "package successful prototypes for effective handoff" responsibility is key for operations professionals, emphasizing the need for structured, documented, and version-controlled output that can be easily understood and integrated by a production development team. This implies a need for clear process documentation and a focus on creating "production-ready" prototypes, not just experimental code.

🎓 Skills & Qualifications

Education: Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Data Science, or a closely related field, OR equivalent demonstrated experience. Recent graduates with strong project portfolios are encouraged to apply.

Experience: 0-2 years of experience in software development, AI development, or related technical fields. Demonstrated ability to take an idea from concept to a working prototype through coursework, internships, hackathons, personal projects, or professional experience is highly valued.

Required Skills:

• Proficiency with current AI development tools and platforms for creating and refining working solutions.

• Strong judgment to critically assess AI-generated output for accuracy, completeness, and reliability.

• Foundational software development skills, with a preference for experience in TypeScript, React, or Python.

• Ability to work effectively with version control systems (e.g., Git).

• Experience with API concepts, integrations, and basic understanding of hosting and deployment.

• High initiative and comfort navigating ambiguity, evolving requirements, and unfamiliar tools without established playbooks.

• Practical problem-solving skills with the ability to balance speed of delivery with the quality of the solution.

• Excellent communication and collaboration skills, capable of interacting effectively with both technical and non-technical stakeholders.

• Adaptability, curiosity, and a willingness to experiment, learn quickly, and iterate on solutions. Preferred Skills:

• Advanced proficiency in TypeScript, React, or Python.

• Experience with prompt engineering techniques and designing agent workflows.

• Familiarity with data privacy and security best practices in software development.

• Experience with cloud platforms (e.g., AWS, Azure, GCP) for prototyping or deployment.

• Demonstrated ability to critically evaluate AI model outputs and identify limitations.

📝 Enhancement Note: The "recent graduates encouraged to apply" and "preferred but not required at an advanced level" for foundational software development skills clearly indicate an entry-level position. The emphasis on "strong comfort using current AI development tools" and "judgment to recognize when AI-generated output is incomplete, inaccurate, or unreliable" highlights the need for practical, hands-on experience with AI, even if formal academic qualifications are limited.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrate the ability to translate abstract business requirements into functional, working software prototypes.

• Showcase examples of rapid iteration and refinement of solutions based on feedback or testing.

• Include projects that highlight the use of AI tools or techniques to solve a specific problem or automate a process.

• Present prototypes that have clear documentation, explaining the problem, the solution, the tools used, and the outcomes. Process Documentation:

• Evidence of documenting the prototyping process, including the iterative steps, challenges encountered, and solutions implemented.

• Examples of creating clear, concise explanations of how a prototype functions and its intended use for non-technical audiences.

• Documentation that outlines the data sources, AI models, and APIs utilized in a prototype.

• Prototypes that are structured in a way that facilitates a smooth handoff to a production development team, including clear code organization and version history.

📝 Enhancement Note: For an entry-level role heavily focused on prototyping, a portfolio is crucial. The emphasis should be on demonstrating the process of building and iterating, rather than just the final polished product. For this specific role, showcasing projects that leverage AI tools, involve prompt engineering, or integrate with APIs would be highly advantageous. The ability to document the process and prepare for handoff is a key operations-related skill.

💵 Compensation & Benefits

Salary Range: Based on industry benchmarks for AI Prototyping Engineers in the United States with 0-2 years of experience, a competitive salary range is estimated between $70,000 and $95,000 annually. This estimate accounts for the specialized AI skills, the remote work arrangement, and the entry-level experience requirement.

Benefits:

• Comprehensive Health Insurance: Medical coverage to support employee well-being. -