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Full-Stack Developer

Evaluation Criteria

  • Clarity + practicality of architecture
  • Clean data model + API design
  • Async job + storage thinking (uploads, outputs, retries)
  • Security basics (auth, access control, safe downloads)
  • Cost + scalability tradeoffs (MVP → v1)
  • Ability to handle ambiguity + user review flows

Problem 1: Video-to-Notes Platform (Architecture Proposal)

We have long videos (3–4 hours, 200MB+). We need an automated “summary package” per video: Summary.md + highlights (timestamps) + screenshots/clips references, organized per video. READ MORE ABOUT THE PROJECT

Task (No code)

Create a concise architecture proposal for an MVP.

Your Solution must include

  • Minimal user flow (3–5 steps)
  • High-level architecture diagram (UI, API, DB, worker/queue, storage, AI)
  • Job lifecycle (queued → processing → success/failed) + progress reporting
  • Data model (tables/entities only)
  • API list (8–12 endpoints)

Your Solution for problem 1:

You need to put your solution here.

Problem 2: LinkedIn Automation Platform (Architecture + Prompt Spec)

User connects LinkedIn, defines persona/tone, provides topics. System generates 3 post drafts, user approves, schedules, and posts automatically. READ MORE ABOUT THE PROJECT

Task (No code)

Provide:

  1. Architecture proposal for MVP (auth, scheduling, approvals, posting).
  2. How to store prompts provide by GenAI team

Your Solution must include

  • Minimal flow: connect → persona → generate → approve → schedule → post
  • Architecture blocks + key integrations (LinkedIn, LLM, scheduler)
  • Data model (User, Persona, Draft, Schedule, PostLog)
  • API list (8–12 endpoints)

Your Solution for problem 2:

You need to put your solution here.

Problem 3: DOCX Template → Bulk DOCX/PDF Generator Architecture

Users upload Word templates, system detects editable fields, supports single fill and bulk generation via CSV/Sheet, exports DOCX/PDF, provides ZIP + report. READ MORE ABOUT THE PROJECT

Task (No code)

Provide MVP architecture + LLM prompt spec for:

  • Template field detection
  • Field schema generation (types, required, validations)

Your Solution must include

  • Flow: upload template → field review → single generate → bulk generate
  • Architecture blocks (template parser, worker, storage, export service)
  • Data model (Template, TemplateField, BulkRun, RowResult, Artifact)
  • Bulk report format (success/fail + reason)

Your Solution for problem 3:

You need to put your solution here.

Problem 4: Character-Based Video Series Generator (Architecture Proposal)

User defines characters once (image + personality + relationships). For each episode, user provides a short story/situation. System outputs an “episode package” (script, scenes, assets list, voiceover plan) and optionally a final video. READ MORE ABOUT THE PROJECT

Task (No code)

Create a small architecture proposal for MVP.

Your Solution must include

  • Data model for Character, Relationship, Episode, Scene, Asset
  • Pipeline flow: story → scene breakdown → dialogues → asset plan → render plan
  • Consistency strategy (character memory, style guide, asset reuse)
  • MVP scope vs v1 scope (what you would ship first)

Your Solution for problem 4:

You need to put your solution here.