Design Technologist - 2026 Fall Coop

📍 Job Overview

Job Title: Design Technologist - 2026 Fall Coop

Company: Motorola Solutions

Location: Illinois, US Offsite (with remote flexibility across the US)

Job Type: Intern (Full-Time)

Category: Design Technology, Software Engineering, AI/ML

Date Posted: May 11, 2026

Experience Level: 0-2 Years (Co-op/Internship)

Remote Status: Remote OK

🚀 Role Summary

• This co-op position focuses on blending design principles with advanced technical execution, particularly in leveraging Large Language Models (LLMs) and modern web frameworks for rapid prototyping.

• The role requires a technical architect with a strong design sensibility, capable of building functional, data-driven prototypes that prove the technical viability of innovative interface concepts.

• Key responsibilities include integrating AI models (LLMs, diffusion models, vector databases) into user-facing applications and optimizing AI performance through prompt engineering and RAG flows.

• This position serves as a critical link between UX design and engineering, translating conceptual designs into scalable technical specifications and providing a builder's perspective to design critiques.

📝 Enhancement Note: This role is framed as a "Design Technologist" co-op, indicating a strong emphasis on the intersection of design and engineering. The focus on AI, LLMs, and prototyping suggests a forward-thinking team aiming to build functional proof-of-concepts rather than static mockups. The "technical architect with a designer's soul" description highlights the dual requirement for robust coding skills and an understanding of user experience principles. The "living prototypes" and "functional core" terminology emphasize the hands-on, build-oriented nature of this internship.

📈 Primary Responsibilities

• Develop high-fidelity, functional prototypes using modern web frameworks (React, TypeScript, Node.js) to demonstrate technical feasibility of design concepts.

• Integrate cutting-edge AI technologies, including LLMs, diffusion models, and vector databases, into interactive user interfaces.

• Optimize AI performance by refining prompts, implementing Retrieval-Augmented Generation (RAG) flows, and fine-tuning model parameters to enhance user experience.

• Act as a technical liaison, translating UX wireframes, design requirements, and user research insights into actionable technical specifications for engineering teams.

• Collaborate with designers and researchers early in the ideation phase to assess technical feasibility and provide a developer's perspective on proposed concepts.

• Research and document emerging AI models, APIs, developer tools, and best practices to maintain the team's leadership in technological innovation.

• Build tools and applications that go beyond traditional design software (like Figma) to create "living" prototypes that showcase dynamic functionality.

📝 Enhancement Note: The responsibilities emphasize hands-on development and integration of AI technologies, moving beyond theoretical concepts to practical application. The focus on "optimizing prompts and RAG flows" and "manipulating model parameters" indicates a deeper dive into AI implementation than simply calling an API. The requirement to translate UX wireframes into technical specifications highlights the bridge-building aspect of the role.

🎓 Skills & Qualifications

Education:

• Currently pursuing a Master's degree in Computer Science, Software Engineering, Human-Computer Interaction (HCI), or a closely related technical field.

• A minor or concentration in Design is considered a significant advantage.

• Must have a graduation date of December 2026 or later.

Experience:

• Academic or project-based experience in developing functional prototypes and web applications.

• Exposure to building and deploying full-stack applications.

Required Skills:

• Front-end Development: Strong proficiency in React, TypeScript, and modern JavaScript.

• Back-end Development: Comfort with Node.js for building server-side logic and APIs.

• Full-stack Environment: Ability to set up and manage a full-stack development environment independently.

• AI API Integration: Demonstrated experience in utilizing AI APIs and understanding their functionalities.

• Prompt Engineering: Hands-on experience crafting, testing, and refining prompts for specific, reproducible AI outputs.

• Technical Design Translation: Ability to interpret UX wireframes and design specifications into technical requirements.

• Problem-Solving: Strong analytical and problem-solving skills for technical feasibility assessments.

Preferred Skills:

• Python Proficiency: Experience with Python for scripting, data processing, and AI/ML workflows.

• Data Architecture: Familiarity with vector databases or the architectural concepts behind Retrieval-Augmented Generation (RAG).

• Design Tool Integration: Experience working with Figma or similar design tools, with an understanding of how to integrate AI capabilities into prototyping workflows.

• Hackathon/Competition Experience: Participation in hackathons, coding competitions, or AI-focused build sprints demonstrating rapid iteration and practical application.

• Interaction Design Fundamentals: Basic understanding of visual hierarchy, interaction design principles, and user-centric design thinking.

📝 Enhancement Note: The requirements clearly prioritize a strong technical foundation in modern web development (React, TypeScript, Node.js) coupled with practical AI experience, specifically prompt engineering and API integration. The emphasis on completing a Master's degree by December 2026 indicates the target audience is graduate students actively pursuing advanced technical education. The distinction between "required" and "preferred" skills helps candidates prioritize their preparation.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• A comprehensive portfolio is mandatory, showcasing end-to-end technical execution and project impact.

• Focus on demonstrating live web applications, functional prototypes, and technical experiments, rather than solely static mockups or theoretical case studies.

• Include examples of projects where you have integrated AI models or APIs to create dynamic user experiences.

Process Documentation:

• Demonstrate your process for translating design concepts into functional code and technical specifications.

• Provide evidence of your prompt engineering methodology, including how you test, iterate, and refine prompts for optimal AI output.

• Document your approach to setting up full-stack development environments and integrating various APIs and services.

• Showcase any research or documentation you've created on emerging AI technologies, APIs, or developer tools.

• If applicable, illustrate your workflow for integrating design tools like Figma with AI-powered development processes.

📝 Enhancement Note: The portfolio requirement is critical and heavily weighted towards practical, demonstrable work. The emphasis on "live web apps and technical experiments" over "static mockups" means candidates need to showcase functional code and interactive prototypes. This aligns with the role's focus on building the "functional core" of future interfaces.

💵 Compensation & Benefits

Salary Range: $30.00 USD - $36.00 USD per hour.

This range is based on the target base hourly rate provided for this co-op position. Actual compensation may vary based on factors such as job-related knowledge, skills, and experience.

Benefits:

As a co-op student, benefits typically include:

• Paid internship/co-op position.

• Opportunities for professional development and networking.

• Exposure to cutting-edge AI and design technology.

• Potential for future employment opportunities within Motorola Solutions.

Working Hours:

• This is a full-time position, implying approximately 40 hours per week.

• Specific daily schedules may be flexible, but require consistent availability during core business hours for collaboration.

📝 Enhancement Note: The salary range is explicitly stated, providing transparency for candidates. While typical intern benefits are listed, the primary value proposition for this role lies in the educational experience, skill development, and exposure to advanced technologies rather than traditional employee benefits. The "Candidate can reside anywhere in the US" note indicates a strong remote work allowance for this co-op.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology, Public Safety, Communications, Software & Hardware Solutions. Motorola Solutions is a key player in providing mission-critical communication and intelligent safety solutions for public safety and enterprise customers worldwide.

Company Size: Motorola Solutions is a large, global enterprise, indicated by its extensive operations and workforce. This size offers stability and a broad scope for impact.

Founded: Motorola Solutions has a long history, tracing its roots back to the early days of radio and mobile communication. This heritage implies a culture of innovation and resilience.

Team Structure:

• The "Experience Design & Research" team is multidisciplinary, comprising Industrial Designers, UX/CX Designers, Researchers, and Human Factors practitioners.

• This specific role, "Design Technologist," likely sits at the intersection of this design team and engineering/software development teams.

• The team embraces the transformative potential of Artificial Intelligence, indicating a forward-thinking and innovative approach to product development.

Methodology:

• The team focuses on a user-centric approach, driven by deep understanding of user needs and insightful data.

• Design and technical feasibility are integrated early in the process, with a "builder's perspective" informing design critiques.

• Rapid prototyping and iterative development using modern frameworks and AI are core to their methodology.

• Emphasis is placed on documenting emerging technologies and maintaining a leading edge in AI and interface development.

Company Website: https://www.motorolasolutions.com/

📝 Enhancement Note: Motorola Solutions is a well-established technology leader with a strong focus on public safety and mission-critical solutions. The Experience Design & Research team's structure suggests a collaborative environment where design and technology are deeply intertwined. The team's embrace of AI indicates a commitment to innovation and staying at the forefront of technological advancements.

📈 Career & Growth Analysis

Operations Career Level: This is an internship/co-op role designed for individuals early in their technical or design technology career path. It offers foundational experience in a specialized, high-demand area.

Reporting Structure: The Design Technologist will likely report to a manager or lead within the Experience Design & Research team, with close collaboration with senior designers and engineers.

Operations Impact: While an intern, the role's impact is centered on proving the technical feasibility of new AI-driven interface concepts and contributing to the development of next-generation products. The work directly influences the early stages of product development and innovation.

Growth Opportunities:

• Skill Development: Deepen expertise in React, TypeScript, Node.js, and gain practical, hands-on experience with LLMs, prompt engineering, and RAG.

• Technical Breadth: Learn to bridge the gap between design and engineering, understanding the full lifecycle of product ideation and prototyping.

• Industry Exposure: Gain invaluable experience within a leading technology company focused on critical communication and safety solutions.

• Networking: Build connections with experienced professionals in design, research, and software engineering.

• Potential for Future Roles: Successful interns often receive consideration for full-time positions upon graduation.

📝 Enhancement Note: This co-op is a significant stepping stone for students looking to specialize in the rapidly growing field of AI-driven design and development. The emphasis on practical application and exposure to advanced technologies provides a strong foundation for future roles in software engineering, AI/ML, or UX engineering.

🌐 Work Environment

Office Type: While the role is remote-friendly and candidates can reside anywhere in the US, Motorola Solutions also maintains physical office locations. For co-op students working remotely, the environment will be home-based, requiring self-discipline and effective remote collaboration tools.

Office Location(s): While the primary posting location is Illinois, US Offsite, the company has broad operations across the US, including California, North Carolina, New York, and Louisiana, suggesting potential for hybrid or in-office experiences depending on team structure and business needs.

Workspace Context:

• Remote Collaboration: Expect to use video conferencing, instant messaging, and project management tools extensively.

• Technical Tools: Access to necessary software licenses and potentially cloud development environments.

• Team Interaction: Regular virtual meetings, design critiques, and code reviews with team members.

• Innovative Atmosphere: Work within a team that is actively exploring and implementing cutting-edge AI technologies.

Work Schedule: Full-time (approx. 40 hours/week), with potential for some flexibility in daily start/end times, but requiring availability for team meetings and collaborative sessions during core business hours.

📝 Enhancement Note: The remote-friendly nature of this co-op is a significant aspect, offering flexibility to candidates across the US. This requires a proactive approach to communication and collaboration within a virtual team setting.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Resume and portfolio review to assess technical skills, academic background, and alignment with role requirements.

• Technical Interview(s): Expect in-depth discussions on your programming skills (React, TypeScript, Node.js), AI/ML concepts, prompt engineering experience, and problem-solving abilities. This may include live coding challenges or whiteboard exercises.

• Design/Technical Collaboration Exercise: You might be asked to discuss how you would approach a given design challenge from a technical feasibility perspective, or how you would translate a wireframe into a functional prototype.

• Behavioral Interview: Assessment of your soft skills, teamwork capabilities, and cultural fit with Motorola Solutions' values.

• Final Interview: Potentially with a hiring manager or senior team member to discuss career aspirations and overall fit.

Portfolio Review Tips:

• Highlight Technical Depth: Clearly showcase the code behind your projects. Provide links to GitHub repositories or live demos.

• Demonstrate AI Integration: Detail your use of LLMs, APIs, prompt engineering, and any RAG implementations. Explain the specific challenges and how you overcame them.

• Showcase Prototyping Process: Walk through your methodology for building "living" prototypes, from concept to functional output. Explain your tech stack choices.

• Explain Impact: Quantify results where possible (e.g., performance improvements, successful concept validation).

• Tell a Story: Structure your portfolio entries to narrate the problem, your approach, the technical challenges, your solutions, and the outcome.

Challenge Preparation:

• Coding Proficiency: Brush up on data structures, algorithms, and common JavaScript/TypeScript patterns. Practice coding challenges focused on React and Node.js.

• AI Concepts: Review core concepts of LLMs, natural language processing, prompt engineering techniques, and RAG. Understand API interactions and model parameter tuning.

• System Design Basics: Be prepared to discuss how you would architect a simple full-stack application or integrate an AI service.

• Design Thinking: Understand the fundamentals of user-centric design, interaction design, and how to translate user needs into technical requirements.

📝 Enhancement Note: The interview process will likely be rigorous, assessing both technical coding skills and practical application of AI technologies. The portfolio is paramount, serving as the primary evidence of your capabilities. Candidates should be prepared to discuss their technical decisions and the "how" and "why" behind their projects.

🛠 Tools & Technology Stack

Primary Tools:

• Front-end Frameworks: React (primary), potentially other modern JavaScript frameworks.

• Languages: TypeScript (primary), JavaScript, Node.js, Python (preferred).

• AI/ML Technologies: Large Language Models (LLMs) (e.g., OpenAI API, Google AI), Diffusion Models, Vector Databases (e.g., Pinecone, Weaviate, ChromaDB), Retrieval-Augmented Generation (RAG) frameworks.

• Development Environment: Node.js, npm/yarn, potentially Docker for containerization.

• Version Control: Git, GitHub/GitLab/Bitbucket.

Analytics & Reporting:

CRM & Automation:

• Not directly applicable to this technical prototyping role, but awareness of how prototypes might eventually integrate into larger systems is helpful.

📝 Enhancement Note: The technology stack is heavily skewed towards modern web development (React, TypeScript, Node.js) and cutting-edge AI technologies. Proficiency in these areas is essential. Experience with Python and data architecture concepts like vector databases and RAG will significantly differentiate candidates.

👥 Team Culture & Values

Operations Values:

• Innovation: A strong drive to explore and implement new technologies, particularly in AI, to solve complex problems.

• User-Centricity: A commitment to understanding user needs and translating them into intuitive and effective technological solutions.

• Collaboration: A belief in cross-functional teamwork, where designers, researchers, and engineers work together seamlessly.

• Technical Excellence: A dedication to building robust, functional, and scalable technical solutions.

• Continuous Learning: An emphasis on staying ahead of industry trends and continuously acquiring new skills in a rapidly evolving technological landscape.

Collaboration Style:

• Cross-functional Integration: Close partnerships between design and engineering teams are fundamental.

• Iterative Feedback: A culture of regular design critiques and code reviews to foster improvement and shared understanding.

• Knowledge Sharing: Encouraging team members to share insights, research findings, and technical best practices.

• Prototyping-Driven: A methodology that relies on building and testing functional prototypes to validate ideas and gather feedback.

📝 Enhancement Note: The team culture emphasizes innovation, collaboration, and a strong technical foundation. The "design technologist" role is positioned to be a key enabler of this culture by bridging creative design with practical, AI-powered development.

⚡ Challenges & Growth Opportunities

Challenges:

• Rapidly Evolving AI Landscape: Staying current with the fast pace of AI model development, new APIs, and best practices.

• Bridging Design and Code: Effectively translating abstract design concepts into concrete, functional code, and vice versa.

• Technical Feasibility Assessment: Accurately evaluating the technical viability of novel design ideas within project constraints.

• Optimizing AI Performance: Fine-tuning AI models and prompts to achieve desired user experience outcomes, which can be complex and iterative.

• Remote Collaboration: Maintaining effective communication and productivity within a distributed team environment.

Learning & Development Opportunities:

• AI Specialization: Deepen expertise in LLMs, prompt engineering, RAG, and other AI technologies through practical application.

• Full-Stack Development Skills: Enhance proficiency in React, TypeScript, and Node.js by building complex prototypes.

• Product Development Lifecycle: Gain insight into how user needs are translated into technical solutions within a large technology company.

• Mentorship: Learn from experienced designers, researchers, and engineers at Motorola Solutions.

• Portfolio Building: Create compelling projects that will be valuable assets for future career opportunities.

📝 Enhancement Note: This role presents excellent opportunities to tackle cutting-edge technical challenges in AI and design, offering significant growth in specialized, high-demand skill sets.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you had to translate a complex user experience design into a functional technical implementation. What were the challenges and how did you overcome them?"

• "How would you approach building a functional prototype that uses an LLM to generate personalized content based on user input? What technologies would you use and why?"

• "Imagine a designer proposes a feature that seems technically infeasible. How would you assess its feasibility and communicate your findings constructively?"

Company & Culture Questions:

• "What interests you most about Motorola Solutions and our mission to create safer communities?"

• "How do you see AI impacting the future of user interfaces, and what role do you want to play in that evolution?"

Portfolio Presentation Strategy:

• Structure Your Narrative: For each project, clearly outline the problem, your role, the technical approach, the AI/design technologies used, key challenges, your solutions, and the outcome/impact.

• Live Demos are Key: Be prepared to walk through your live applications or prototypes, showcasing functionality and explaining your code.

• Explain Technical Choices: Articulate why you chose specific frameworks, languages, or AI models.

• Highlight AI Implementation Details: Detail your prompt engineering strategies, RAG implementation, or any other AI-specific work. Show how it improved the user experience.

• Be Ready for Code Questions: Anticipate questions about specific snippets of your code or architectural decisions.

📝 Enhancement Note: Interview preparation should focus heavily on demonstrating practical application of technical skills, a deep understanding of AI concepts, and the ability to articulate technical decisions and processes clearly. The portfolio is the central piece of evidence.

📌 Application Steps

To apply for this Design Technologist co-op position:

• Submit your application through the provided link on the Motorola Solutions careers portal.

• Tailor your resume to highlight your experience with React, TypeScript, Node.js, AI APIs, prompt engineering, and any relevant prototyping projects. Quantify achievements where possible.

• Curate your portfolio to showcase your strongest technical projects, focusing on live applications, functional prototypes, and AI integrations. Ensure GitHub links or live demos are readily accessible.

• Prepare a concise narrative for each portfolio project, explaining your technical approach, challenges, and outcomes. Practice presenting these projects clearly and concisely.

• Research Motorola Solutions and its mission. Understand their product lines and how AI might be integrated into their offerings. Prepare to discuss your interest in the company and the role.

• Practice coding exercises and be ready to discuss AI concepts and prompt engineering strategies during technical interviews.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.