Rapid Prototyping Engineer (Junior / Entry Level)

📍 Job Overview

Job Title: Rapid Prototyping Engineer (Junior / Entry Level)

Company: Fulfillment IQ

Location: Toronto, Ontario, Canada

Job Type: Full-Time

Category: Software Engineering / Operations Technology

Date Posted: January 20, 2026

Experience Level: Junior / Entry Level (1-3 Years)

Remote Status: Remote Solely

🚀 Role Summary

• This role focuses on the rapid development and validation of functional prototypes within the logistics and supply chain technology sector, leveraging modern full-stack development practices.

• The position emphasizes leveraging AI-assisted coding tools to accelerate the creation of proof-of-concepts, underscoring a commitment to innovation and efficiency in software development.

• A critical aspect of this role involves comprehensive full-stack debugging and problem-solving across frontend, backend, API, and database layers to ensure prototype reliability.

• The engineer will work in agile, time-boxed cycles, iterating quickly based on stakeholder feedback to validate technical directions and prepare for potential production environments.

📝 Enhancement Note: While the title is "Rapid Prototyping Engineer," the core responsibilities and required skills in Python, Next.js, and MongoDB, along with debugging and AI-assisted development, strongly align with a specialized junior software engineering role focused on GTM enablement and internal tooling optimization within an operations-centric technology consultancy. The emphasis on "prototypes" suggests a role that bridges conceptualization with tangible, functional applications, often seen in GTM strategy validation or internal process improvement initiatives.

📈 Primary Responsibilities

• Develop quick, functional proof-of-concepts (POCs) and prototypes using Python (FastAPI preferred), Next.js/React, and MongoDB, adhering to modern full-stack development patterns.

• Integrate various data sources, SDKs, and public APIs into working prototype applications to demonstrate technical feasibility and potential business value.

• Implement simple, yet effective, front-end UIs for demonstrations and functional flow validation using Next.js, Tailwind CSS, React Hooks, and basic component libraries.

• Conduct thorough full-stack debugging across frontend console errors, backend logs, API gateway issues, environment variables, Dockerized services, and MongoDB queries.

• Troubleshoot and resolve performance bottlenecks, CORS errors, and build/runtime failures in both local development and cloud-based environments.

• Write structured prompts for AI coding assistants (e.g., GitHub Copilot, ChatGPT) to generate, refactor, and optimize code, while critically evaluating AI-generated output for correctness, security, and maintainability.

• Document useful AI prompts, patterns, and prototype components to foster knowledge sharing and reuse within the engineering team.

• Participate actively in lightweight peer reviews and code walkthroughs, adhering to Git branching workflows, commit hygiene, and documentation standards.

• Prepare prototypes for potential handoff to production teams by writing clear README files, setup instructions, and design decision notes.

• Collaborate effectively within 1–2 week time-boxed development cycles, participating in frequent demos and incorporating stakeholder feedback to refine prototypes rapidly.

📝 Enhancement Note: The responsibilities highlight a blend of development, debugging, and AI utilization, typical of roles supporting GTM initiatives by quickly validating new technology integrations or building internal tools that enhance sales and customer success operations. The emphasis on "prototypes" and "proof-of-concepts" suggests a focus on rapid iteration to test hypotheses or demonstrate value before full-scale development.

🎓 Skills & Qualifications

Education:

Experience:

Required Skills:

• Strong programming proficiency in:

  • Python (experience with FastAPI, Flask, or similar frameworks)
  • Next.js / React (TypeScript or JavaScript)
  • MongoDB (demonstrated ability with queries, indexing, and basic schema design)

• Proven experience integrating and debugging:

  • REST APIs
  • Webhooks
  • Authentication mechanisms (e.g., Auth0, Keycloak, JWT, OAuth)

• Demonstrated ability to debug full-stack issues, including:

  • Frontend console errors and network requests
  • Backend logs, exceptions, and stack traces
  • Database query performance and errors
  • Network configuration issues (CORS, headers, environment variables)

• Familiarity with AI-assisted coding tools such as GitHub Copilot, ChatGPT, Claude, or similar, including the ability to write effective prompts and critically evaluate generated code.

• Working knowledge of Docker fundamentals (build, run, logs, Docker Compose).

• Experience with version control systems, particularly Git, including branching workflows and commit best practices.

• Proficiency with modern development tooling, including:

  • Postman / Thunder Client for API testing
  • Chrome DevTools for frontend debugging
  • MongoDB Compass / Atlas for database management

Preferred Skills:

• Basic understanding of Machine Learning or Large Language Model (LLM) concepts, including embeddings or vector databases (e.g., Pinecone, Chroma).

• Experience with serverless functions (e.g., Vercel, AWS Lambda, Azure Functions).

• Familiarity with Tailwind CSS or modern component frameworks (e.g., Shadcn UI, Material UI).

• Basic knowledge of GraphQL.

• Exposure to CI/CD concepts, such as GitHub Actions.

• Familiarity with cloud platforms (Azure, AWS, or GCP).

📝 Enhancement Note: The requirement for AI-assisted coding and debugging across the full stack, coupled with the "nice to have" skills in ML/LLMs and serverless, positions this role as one that could support GTM operations by rapidly building tools for data analysis, customer engagement, or internal process automation. The emphasis on debugging is crucial for ensuring the reliability of these early-stage solutions.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrations of functional prototypes built using Python, Next.js, and MongoDB, showcasing end-to-end application logic.

• Case studies or examples detailing the debugging process for complex full-stack issues, highlighting problem-solving methodologies and resolution strategies.

• Examples of effective prompt engineering for AI coding assistants, demonstrating how AI was used to accelerate development or improve code quality.

• Projects that illustrate integration with external APIs or data sources, emphasizing data flow and consistency.

Process Documentation:

• Candidates should be prepared to discuss their approach to rapid iteration and development cycles, including how they manage feedback and prioritize tasks within time-boxed periods.

• Ability to articulate the process of debugging across different layers of a technology stack (frontend, backend, database, infrastructure).

• Understanding of version control workflows (Git) and their role in collaborative development and maintaining code integrity.

• Experience with documenting technical decisions, setup procedures, and prototype functionality for knowledge transfer.

📝 Enhancement Note: For a "Rapid Prototyping Engineer," the portfolio should emphasize speed, functionality, and the ability to quickly iterate. For operations roles, this translates to showing proficiency in building tools that can quickly address business needs, test hypotheses, or streamline workflows, even if they are not production-ready. The ability to document the process of rapid development and debugging is key.

💵 Compensation & Benefits

Salary Range:

Benefits:

• Supplementary Health Benefits: Comprehensive coverage for medical, dental, and vision care.

• Wellness Program: Resources and support for employee well-being.

• Paid Vacation: Generous paid time off for rest and rejuvenation.

• Sick Leave: Support for personal health needs.

• Statutory Holidays: Paid time off for public holidays.

• CPP Contributions: Contributions to the Canada Pension Plan.

• Additional Retirement Programs: Options for further retirement savings and planning.

• Learning & Development Budget: Funds allocated for professional growth, courses, certifications, and conferences.

• Internet and Workstation Reimbursement: Support for home office setup and connectivity.

• Anniversary Rewards: Recognition for tenure and commitment.

Working Hours:

• Standard full-time hours are typically 40 hours per week, with flexibility often afforded to remote employees to manage their work schedules effectively, provided project deadlines and collaboration needs are met.

📝 Enhancement Note: The salary range is an estimate based on general market data for a junior full-stack developer in Toronto. Actual compensation may vary based on the candidate's specific qualifications, interview performance, and the company's compensation philosophy. The benefits listed are directly from the job description and are comprehensive for a remote role.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology Consulting, Logistics & Supply Chain Technology. Fulfillment IQ operates at the intersection of technology and logistics, providing consultancy services and custom software solutions to brands, retailers, and 3PLs. This focus means the company culture is likely to be dynamic, problem-solution oriented, and driven by client needs and technological advancements in the supply chain domain.

Company Size: The provided LinkedIn data indicates a company size of 51-200 employees. This range suggests a growing company that offers a balance between the structure of a larger organization and the agility and collaborative environment of a smaller one. For operations professionals, this often means more direct impact, broader exposure to different projects, and closer interaction with leadership.

Founded: Founded in 2021, Fulfillment IQ is a relatively new company. This implies a startup or early-stage growth environment, characterized by rapid innovation, evolving processes, and a strong emphasis on building foundational systems and culture.

Team Structure:

• The engineering team is likely structured to support client projects and internal product development, with specialists in various technology stacks and domains.

• Reporting structures are probably relatively flat, encouraging direct communication and collaboration across roles, including engineers, strategists, and logistics experts.

Methodology:

• Data analysis and insights are central to the company's consulting approach, informing technology stack selections and solution designs.

• Workflow planning and optimization are key components of their client services, aiming to improve efficiency and effectiveness in logistics operations.

• Automation and efficiency practices are core to their technology solutions, leveraging modern tools and techniques to streamline supply chain processes.

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

📝 Enhancement Note: The company's focus on logistics technology and its recent founding suggest a fast-paced, innovative environment. For operations roles, this means opportunities to shape processes and contribute to the development of tools that directly impact supply chain efficiency. The remote-first nature with a collaborative culture is a significant draw.

📈 Career & Growth Analysis

Operations Career Level: This "Junior / Entry Level" role is positioned as a foundational step within a technology-focused engineering team. It provides an opportunity to build core full-stack development skills, gain practical experience in rapid prototyping, and understand the application of technology within the logistics and supply chain domain. Success in this role can lead to more senior engineering positions or specialized roles within the company's technology practice.

Reporting Structure: The engineer will likely report to an Engineering Lead or Manager who oversees prototype development and engineering initiatives. There will be frequent interaction with project managers, consultants, and potentially client stakeholders during demo cycles.

Operations Impact: While not a direct operations role, this position has a significant indirect impact on operations. By rapidly building and validating prototypes, the engineer helps validate technical directions for operational improvements, custom software solutions, and technology stack selections for clients. This work directly influences the efficiency, scalability, and effectiveness of logistics and supply chain operations undertaken by Fulfillment IQ's clients.

Growth Opportunities:

• Operations Skill Advancement: Gain hands-on experience with technologies and platforms critical to modern logistics operations, developing a strong understanding of supply chain challenges and technology solutions.

• Technical Specialization: Opportunity to deepen expertise in Python, Next.js, React, MongoDB, and potentially explore emerging areas like AI/ML, serverless computing, and cloud technologies through project work and company-provided training.

• Leadership Potential: As proficiency grows, there may be opportunities to lead prototype development efforts, mentor junior engineers, contribute to architectural discussions, and transition into roles with greater responsibility in client-facing projects or internal product development.

📝 Enhancement Note: This role is a strong entry point for individuals interested in the operational impact of technology. The growth path focuses on building robust software engineering skills that can be applied to solve complex operational challenges in the logistics sector.

🌐 Work Environment

Office Type: Fulfillment IQ is a "remote-first" organization. This implies a distributed team structure where employees work from their own locations, fostering autonomy and flexibility.

Office Location(s): While the job is posted for Toronto, Ontario, Canada, the "remote solely" designation suggests that physical presence in Toronto is not required. The company may have a legal entity or administrative presence there, but employees can work from anywhere, with potential preferences for candidates within specific time zones for collaboration.

Workspace Context:

• The remote-first environment encourages self-directed work and requires strong personal organization and communication skills.

• Access to modern development tools, including AI coding assistants and cloud platforms, is provided to enhance productivity.

Work Schedule:

• The standard work week is 40 hours, but the remote-first nature often allows for flexible scheduling. Employees are expected to manage their time to meet project deadlines, attend critical meetings, and collaborate effectively with colleagues across different time zones.

📝 Enhancement Note: The remote-first aspect is a significant differentiator, appealing to candidates seeking work-life balance and autonomy. Operations professionals often thrive in environments that support flexible work arrangements, allowing for focused deep work.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your application, resume, and potentially a brief introductory call to assess basic qualifications and cultural fit.

• Technical Assessment: This may involve a coding challenge (live or take-home) focusing on Python, Next.js, and debugging skills, or a technical deep-dive interview with an engineering team member.

• Portfolio Review & Discussion: A session where you present your past projects, prototypes, and problem-solving examples. Emphasis will be on your approach to rapid development, debugging, and AI tool usage.

• Team/Hiring Manager Interview: A discussion focused on your problem-solving approach, collaboration style, understanding of the role's impact, and alignment with Fulfillment IQ's culture.

• Final Interview: Potentially a discussion with senior leadership for final assessment.

Portfolio Review Tips:

• Highlight Rapid Development: Showcase projects where you quickly built functional prototypes or proof-of-concepts. Emphasize speed and iteration.

• Demonstrate Debugging Prowess: Select a project where you encountered and resolved complex full-stack bugs. Clearly articulate your diagnostic process and the tools you used.

• Showcase AI Integration: Include examples where you effectively used AI coding assistants. Detail the prompts used, the output, and how you verified/refined the AI-generated code.

• Focus on Full-Stack: Present projects that demonstrate your ability to work across the frontend, backend, and database layers.

• Explain Your Process: Be ready to walk through your thought process, development methodology, and how you incorporated feedback.

Challenge Preparation:

• Practice Debugging Scenarios: Familiarize yourself with common full-stack debugging techniques and tools for Python, Node.js/Next.js, and MongoDB.

• Refine Prompt Engineering: Practice writing clear, specific prompts for AI coding assistants to generate various types of code and solutions.

• Prepare API Integration Examples: Be ready to discuss how you've integrated frontend applications with backend APIs.

• Review Core Technologies: Refresh your knowledge of Python (FastAPI), Next.js/React, and MongoDB fundamentals.

📝 Enhancement Note: The emphasis on a portfolio review and debugging skills suggests that Fulfillment IQ values practical, hands-on problem-solving and the ability to quickly translate ideas into functional code. For operations-minded candidates, this means framing projects around solving business problems or improving efficiency.

🛠 Tools & Technology Stack

Primary Tools:

• Backend Frameworks: Python (FastAPI preferred, Flask also acceptable)

• Frontend Frameworks: Next.js / React

• Databases: MongoDB (NoSQL document database)

• API Technologies: REST APIs, GraphQL (preferred)

• AI Coding Assistants: GitHub Copilot, ChatGPT, Claude, Cursor

• Development Environment: VS Code

Analytics & Reporting:

• While not explicitly mentioned for this role, candidates should be comfortable with tools that facilitate debugging and performance analysis, such as:
  • Chrome DevTools (for frontend performance and debugging)
  • Logging tools (for backend error tracking)

CRM & Automation:

DevOps & Cloud Basics:

• Containerization: Docker (fundamentals: build, run, logs, Docker Compose)

• CI/CD: GitHub Actions or similar CI basics.

• Cloud Platforms: Familiarity with Azure, AWS, or GCP is a plus.

Collaboration & Productivity:

• API Testing: Postman / Thunder Client

• Version Control: Git

📝 Enhancement Note: The technology stack is modern and full-stack oriented. Proficiency in these tools, especially Python, Next.js, and MongoDB, is crucial. The inclusion of AI coding assistants highlights a forward-thinking approach to development efficiency.

👥 Team Culture & Values

Operations Values:

• Curiosity & Experimentation: A strong emphasis on exploring new technologies and approaches, particularly in the rapid prototyping phase.

• Fast Learning: The ability to quickly acquire new skills and adapt to evolving project requirements is paramount in a fast-paced consulting environment.

• Clear Execution: Despite the focus on speed, there's an expectation of delivering functional and reliable prototypes that validate technical directions effectively.

• Collaboration: Working effectively within a distributed team, sharing knowledge, and contributing to a positive team environment.

• Problem-Solving: A core value driving the company's approach to client challenges and technical development.

Collaboration Style:

• Remote-First Communication: Reliance on digital tools (Slack, video conferencing, shared documents) for communication and collaboration.

• Agile & Iterative: Working in short cycles with frequent demos and feedback loops, fostering continuous improvement.

• Knowledge Sharing: Encouraging the sharing of useful AI prompts, code patterns, and debugging techniques across the team.

• Peer Review: Lightweight code walkthroughs and peer feedback to maintain code quality and share best practices.

📝 Enhancement Note: The culture emphasizes agility, learning, and innovation, which is highly beneficial for individuals looking to make a tangible impact in a growing technology consultancy. For operations-focused candidates, this culture aligns with a proactive and adaptable approach to problem-solving.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Speed and Quality: The primary challenge is building prototypes rapidly while ensuring they are functional, reliable, and maintainable enough to validate technical direction.

• Debugging Complex Issues: Effectively diagnosing and resolving full-stack bugs across a diverse technology stack under time pressure.

• Leveraging AI Responsibly: Mastering the use of AI coding assistants to accelerate development without compromising code quality, security, or introducing subtle errors.

• Adapting to Evolving Client Needs: Quickly understanding and prototyping solutions for a variety of logistics and supply chain challenges presented by different clients.

Learning & Development Opportunities:

• Hands-on Experience: Gaining practical, in-depth experience with a modern full-stack technology stack (Python, Next.js, MongoDB) and cutting-edge AI development tools.

• Mentorship: Receiving guidance from senior engineers on best practices, advanced debugging techniques, and career development.

• Exposure to Logistics Tech: Developing a strong understanding of the unique technological challenges and opportunities within the logistics and supply chain industry.

• AI/ML Training: Opportunities to explore and learn about AI/ML applications, embeddings, and vector databases, enhancing skills in emerging technologies.

• Cloud Platform Exposure: Gaining familiarity with major cloud providers (AWS, Azure, GCP) through project work.

📝 Enhancement Note: The challenges are inherent to rapid prototyping and debugging, offering significant learning opportunities. The growth path is clearly defined through technical skill development and exposure to advanced technologies.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you had to debug a complex full-stack issue. What was your process, and what tools did you use to resolve it?" (Focus on systematic debugging, tools like Postman, Chrome DevTools, logs, and MongoDB queries).

• "How do you approach using AI coding assistants like GitHub Copilot? What are the benefits, and what are the potential pitfalls you watch out for?" (Emphasize prompt engineering, code verification, and responsible AI usage).

Company & Culture Questions:

• "Why are you interested in rapid prototyping and working with AI coding tools?" (Connect your interest to efficiency, innovation, and fast-paced environments).

• "How do you stay updated with new technologies and development practices?" (Mention continuous learning, industry blogs, and experimentation).

Portfolio Presentation Strategy:

• Structure Your Demos: For each project, clearly state the problem, your solution (prototype), the technologies used, and the outcome or key learnings.

• Detail Your Debugging Process: For debugging examples, use a visual aid or clear narrative to show the symptoms, your diagnostic steps, and how you pinpointed and fixed the issue.

• Showcase AI Prompting: If possible, show examples of prompts you used and the resulting code, explaining why that prompt was effective.

• Emphasize Iteration: Highlight how feedback influenced your prototype's development and how you adapted quickly.

• Be Concise and Focused: Given the "rapid" nature, keep your presentations tight and focused on key achievements and learnings.

📝 Enhancement Note: The interview process will likely assess your technical skills, problem-solving abilities, and how well you fit into a fast-paced, remote-first, and innovative culture. Be prepared to demonstrate practical application of your skills, especially in debugging and leveraging AI.

📌 Application Steps

To apply for this operations-adjacent technology position:

• Submit your application through the provided link on Workable.

• Customize Your Resume: Tailor your resume to highlight your experience with Python, Next.js, MongoDB, full-stack debugging, and any experience with AI coding tools. Quantify achievements where possible (e.g., "Reduced debugging time by X%").

• Prepare Your Portfolio: Select 2-3 key projects that best demonstrate your rapid prototyping, full-stack development, and debugging skills. Be ready to present them clearly and concisely, focusing on your problem-solving approach and technical execution.

• Practice Interview Questions: Review common technical interview questions related to your core skills and prepare answers that showcase your understanding of the full stack and your ability to troubleshoot effectively.

• Research Fulfillment IQ: Understand their business as a logistics and supply chain technology consultancy. Consider how your prototyping skills can contribute to their client solutions and internal operations.

⚠️ 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.