Full-Stack Engineering Intern, AI Retail Systems

DrapeLogic is building AI-powered virtual try-on and assisted selling tools for boutique clothing stores. We help stores let shoppers visualize outfits, compare looks, and use store inventory more effectively across web, admin, and in-store device experiences.

We are looking for a full-stack engineering intern who can work closely with the founder across product engineering, AI-assisted workflows, computer-vision product features, QA, technical documentation, and implementation support.

The ideal intern is not only a coder. They are organized, curious, willing to debug messy product flows, and able to turn rough founder direction into concrete technical work. This role will involve wearing multiple hats across frontend, backend, AI/image workflows, data tooling, product thinking, and release readiness.

This is an early-stage product role: priorities may shift as we test with stores, improve the AI pipeline, and prepare for market. You should be comfortable with ambiguity, fast feedback loops, and practical execution.

• Build and improve product features across web, admin, and in-store device experiences.
• Help test and polish user flows for virtual try-on, product browsing, comparison, photo upload, and store inventory management.
• Support AI and computer-vision workflows related to image processing, model images, try-on quality, and product media.
• Work across frontend, backend, APIs, scripts, data workflows, and internal tools depending on what the product needs most.
• Write technical specs, API documentation, QA notes, and implementation checklists.
• Investigate bugs, reproduce issues, document root causes, and help ship fixes.
• Review frontend code for duplicate components, inconsistent UX, and fragile patterns.
• Support production-readiness work such as data migration checks, configuration cleanup, and release validation.
• Help prepare technical workflows that make it easier for stores to upload, edit, and manage inventory.
• Use AI coding tools responsibly to accelerate implementation while checking the actual product behavior.

• Improve the AI try-on workflow based on real store demos: identify where outputs fail, inspect image inputs, and help make the experience more reliable for boutique owners.
• Build Python scripts or internal tools to analyze product images, model images, and shopper-uploaded photos so poor-quality inputs can be flagged before they hurt try-on results.
• Help create the technical workflow for a boutique to upload inventory, clean product data, attach images, and get a usable store demo running quickly.
• Improve the in-store demo experience across web, admin, and device surfaces so a boutique owner can understand the product without founder hand-holding.
• Investigate AI/image pipeline failures by tracing requests, status updates, media files, model inputs, and user-facing output states.
• Use computer-vision techniques where useful for pose, image-quality, garment, or model-photo checks that can improve virtual try-on quality.
• Turn feedback from pilots and demos into small product changes, technical specs, experiments, and measurable improvements.

• Current student or recent graduate in computer science, software engineering, data science, or a related technical field.
• Comfortable with JavaScript or TypeScript.
• Comfortable with Python or willing to use it for scripting, data workflows, AI experiments, and image-processing tasks.
• Familiarity with React, Next.js, or similar frontend frameworks.
• Able to read an existing codebase and make small, focused changes.
• Strong written communication.
• Careful with testing, edge cases, and user-facing behavior.
• Comfortable working in a fast-moving, ambiguous startup environment.
• Able to use AI coding tools while still understanding, testing, and debugging the code they produce.

• Experience with APIs, databases, or cloud deployment.
• Experience with Playwright, unit tests, or QA workflows.
• Interest or experience in AI, computer vision, image processing, retail technology, or virtual try-on.
• Experience using AI coding tools such as Codex, Claude Code, Cursor, or GitHub Copilot.
• Basic product sense: noticing when an implementation technically works but still feels confusing to a user.

This role is not a pure research internship, a theory-only AI role, or a role where you only build isolated prototypes. The work is practical and product-focused. You will be expected to ship, test, document, and improve real workflows.

Please send your resume, GitHub or portfolio if available, and a short note answering:

1. What is one technical project you built or debugged that you are proud of?
2. How do you approach working in an unfamiliar codebase?
3. Have you used AI coding tools? If yes, how do you check their work?