Full-Stack Engineer for AI Answer-Sheet Evaluation

I’m building an AI product for educational institutions that helps evaluate descriptive / handwritten answer sheets faster and more consistently. The product is intended to support a teacher / evaluator workflow where they can: - Create an exam / evaluation session - Upload: question paper, marking scheme / rubric and scanned student answer sheets - Receive AI-generated outputs for each answer sheet, including: extracted answers question-by-question, suggested marks, grading justifications, confidence flags and inline annotation suggestions / comments tied to relevant answer content - Review the answer sheet in a teacher-facing UI - Edit marks and comments - Add / edit inline annotations directly on the answer sheet - Finalize marks and export results I’m looking for a Full-Stack Engineer who can own the product application and review workflow side of this product. There will be a separate engineer for the AI pipeline. Your role is to build the web application, manage web app hosting, teacher review workflow, answer-sheet viewer, inline annotation UX, backend integration, persistence, and export flow that turns the AI outputs into a usable institution-facing product. You will own the application / product workflow side of the product, including: - exam / evaluation session creation - upload workflows for question paper, rubric, and answer sheets - backend integration with the AI grading pipeline - persistence for exams, answer sheets, question-wise outputs, teacher edits, and final marks - teacher review UI - answer-sheet viewer with inline comments / annotations - result views and export workflows - end-to-end product polish for demos You should think of this as building the teacher-facing operating system around the AI grading engine. Milestone 1 Deliverables — By Week 2 - working basic app for answer sheet uploads and review - backend schema / persistence for exams, answer sheets, AI outputs, and annotations - AI integration path connected end-to-end for sample answer sheets - basic page to inspect question-wise extracted answers, grading outputs, and annotation suggestions - deployable prototype that I can click through and test Milestone 2 deliverables - By Week 4 - support auth and session management - working teacher review screen - editable marks/comments per question - answer-sheet viewer with inline annotation support - persisted teacher overrides and annotation state - answer-sheet navigation and exam-level batch view - cleaner end-to-end product workflow Milestone 3 — By week 6 - final results table / batch view - CSV / Google sheets export for finalized results - Improved polished UI and product readiness - stable end-to-end workflow for institutions to use - Deployed app accessible to allowed users Availability and collaboration requirements - Be available on chat for quick questions, clarifications, and design / implementation discussions - Attend short daily standups / check-ins to share progress, blockers, and next steps - Collaborate effectively with other engineers working on adjacent parts of the product and actively manage dependencies across the AI and application layers - Participate in code reviews for relevant changes made by other engineers so the overall MVP stays coherent and integrated - Handle open-ended product / technical problems as they come up during the project - Comfortable balancing speed with enough structure and quality for a real product