Marketeq Digital

About the Role Marketeq is hiring a Full-Stack AI Engineer Intern Frontend-Focused to support frontend implementation, frontend/API integrations, and AI-assisted full-stack development. This is an unpaid, part-time, graduate-level internship for current Master’s degree students or Master’s graduates only. Applicants must be current U.S. residents and should already have hands-on experience with frontend development, full-stack integrations, and AI-assisted coding tools. This role is full-stack, but the main focus is frontend development.

You should be comfortable building user interfaces, working with modern frontend frameworks, turning Figma designs into responsive screens, connecting frontend screens to backend APIs, and handling common frontend states such as loading, empty, error, validation, and edge cases. You will use tools such as Claude CLI, OpenAI Codex, Cursor, ChatGPT, GitHub Copilot, MCP tools, or similar AI-assisted development tools to help understand documentation, generate implementation plans, build features, debug issues, refactor code, and prepare work for review. You will work alongside engineering and QA teams, contribute to implementation documentation, and learn how real product work moves from requirements, to frontend implementation, to API integration, to review, staging, QA handoff, and release. The role is best suited for someone who is frontend-strong, full-stack capable, AI-tool-fluent, detail-oriented, and serious about becoming a stronger product-minded engineer. Internship Details Role Type: Unpaid Internship Schedule: 15 20 hours per week Duration: 4 6 months Location: 100% Remote Eligibility: Current U.S. residents only Education: Current Master's students or Master's graduates Academic Credit: Supported where available through your institution Start Date: Immediate availability preferred Applicants must be current U.S.

residents and must be currently pursuing or have completed a Master’s degree. Applicants must also be legally authorized to participate in a remote internship in the U.S. We are unable to sponsor visas for this internship. Responsibilities Build frontend features from Figma designs using AI-assisted development workflows Create responsive, accessible, and maintainable user interfaces Integrate frontend applications with existing backend APIs Handle authentication, validation, loading states, error states, permissions, and edge cases Maintain and extend existing components, design systems, and application patterns Use AI coding tools to assist with implementation, debugging, refactoring, testing, and documentation Troubleshoot frontend, backend, and integration issues Perform self-testing before QA handoff Document implementation decisions, assumptions, edge cases, and technical notes Participate in code reviews and incorporate feedback Collaborate with engineering, QA, and product stakeholders Required Qualifications Currently pursuing or completed a Master's degree in Computer Science, Software Engineering, AI, Data Science, Information Technology, HCI, Machine Learning, or a related technical field Current U.S.

resident Minimum 2 years of frontend development experience through coursework, internships, projects, freelance work, open-source contributions, or professional experience Strong proficiency in HTML, CSS, JavaScript, and TypeScript Experience with modern frontend frameworks such as React, Next.js, Vue, Angular, or Svelte Experience translating Figma designs into working applications Experience building responsive web interfaces Experience consuming REST or GraphQL APIs Understanding of frontend architecture, backend integrations, authentication, and deployment workflows Familiarity with OAuth, JWT, sessions, or role-based access control Experience using AI-assisted development tools such as Claude, Codex, Cursor, ChatGPT, GitHub Copilot, or similar Experience with Git, pull requests, and code review workflows Ability to work independently, read documentation, and solve technical problems effectively Portfolio, GitHub profile, or project samples available for review Preferred Qualifications Strong frontend skills with the ability to handle full-stack integrations Experience using AI coding tools in real development workflows Ability to review, debug, and improve AI-generated code Strong UI/UX attention to detail Experience with frontend/API integrations, authentication, validation, and error handling QA-minded approach to software development Ability to document work clearly and communicate technical decisions effectively Experience working within established codebases and engineering standards What You'll Learn Production frontend and full-stack development workflows Design-to-development implementation processes API integration and real-world data flows AI-assisted engineering practices and workflows Code review, QA, staging, and release processes Technical documentation and implementation planning Cross-functional collaboration with engineering and QA teams Best practices for maintaining code quality while leveraging AI tools Nice to Have Accessibility (WCAG) knowledge Frontend performance optimization experience CI/CD experience (GitHub Actions, Vercel, Netlify, AWS, etc.) Familiarity with Sentry, LogRocket, or similar tools Experience with Playwright, Cypress, Postman, or related testing tools Experience with design systems and component libraries Backend experience with Node.js, NestJS, Express, Django, FastAPI, Rails, Spring Boot, or similar frameworks Experience with PostgreSQL, MySQL, MongoDB, Supabase, Prisma, or similar technologies Experience with AI agents, prompt engineering, vector databases, MCP tools, or automation workflows Application Requirements Please submit: Resume GitHub profile, portfolio, or project samples 2 3 examples of frontend or full-stack projects you built Brief summary of your Figma-to-code experience Brief summary of your experience with AI-assisted development tools Brief summary of your experience with API integrations, authentication, or full-stack product features Weekly availability Whether your institution supports academic credit for internships