115 أسطر
5.3 KiB
Markdown
115 أسطر
5.3 KiB
Markdown
# Ghaymah GenAI Engineer — Technical Interview
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**Track:** Generative AI / AI Agents
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**Duration:** 60 minutes
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**Submission:** GitPasha (push to your exam repo)
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**Language:** English or Arabic — your choice (Arabic is encouraged for the ecosystem questions)
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---
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## Welcome 👋
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Welcome to the Ghaymah technical interview. This is a **hands-on, 60-minute** exam — not a whiteboard Q&A. We want to see how you think, what you build, and how you work inside the **Arabic tech ecosystem**, because that is the ecosystem we build for and with.
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You are interviewing to join the team that builds **agents like Cumin** — the AI agent that runs inside a compute sandbox (persistent containers + serverless functions + an object-store workspace) and works across data processing, scraping, conversion, and deployment. In this exam you will:
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1. Introduce yourself to the Arabic tech ecosystem (**Qabilah** + **Mortakaz**).
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2. Design a **memory module** for an agent like Cumin, and show how to use it.
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3. Propose an **Arabic TTS or STT** model + dataset.
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4. Sign up to **Ghaymah**, **deploy a static website**, and build a **LangChain agent** on Ghaymah's GenAI services.
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## What we are evaluating
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| Skill | Where it shows up |
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| Arabic tech ecosystem awareness | Qabilah + Mortakaz tasks |
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| Agent engineering intuition (memory, retrieval, storage trade-offs) | Q1 |
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| Arabic NLP depth (model + dataset selection) | Q2 |
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| Shipping — deploy something live | Q3 + Q4 |
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| Agent building with real tooling (LangChain) | Q5 |
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## The stack you will touch
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| Platform | What it is | URL |
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|---|---|---|
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| **Qabilah (قبيلة)** | Arabic tech social / community platform | https://qabilah.com |
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| **Mortakaz (مُرتكز)** | Directory of ~686 Arab-built products | https://mortakaz.com |
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| **Ghaymah (غيمة)** | Arabic cloud platform (PaaS) | https://ghaymah.systems |
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| **Ghaymah Dashboard** | Where you sign up, get AI models, and deploy | https://deploy.ghaymah.systems |
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## Time budget (60 min total)
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| Task | Folder | Budget |
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|---|---|---|
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| Read this README + set up | — | 5 min |
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| Qabilah profile + check-in | `common-qabilah/` | 3 min |
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| Mortakaz discovery + integration proposal | `common-mortakaz/` | 10 min |
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| Q1 — Cumin memory module design | `q1-cumin-memory/` | 15 min |
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| Q2 — Arabic TTS/STT model + dataset proposal | `q2-arabic-tts-stt/` | 6 min |
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| Q3 — Ghaymah signup | `q3-ghaymah-signup/` | 4 min |
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| Q4 — Deploy a static site on Ghaymah | `q4-static-site-deploy/` | 8 min |
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| Q5 — LangChain agent on Ghaymah's GenAI services | `q5-llm-agent/` | 9 min |
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| **Total** | | **≈ 60 min** |
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> ⏱️ Be honest about your time. A focused, complete 60-minute submission beats a half-finished 2-hour one. We look at commit timestamps.
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## Rules
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1. Work **inside this repo**. Each question has its own folder with a task description and an answer template. Fill in your answers **in place**.
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2. Do not rename or move the question folders.
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3. Never commit real credentials, tokens, or passwords — use placeholders like `<REDACTED>`.
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4. For Q4, commit your actual site source under `q4-static-site-deploy/site/`; for Q5 under `q5-llm-agent/`.
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5. You may use any public resources (docs, model cards, papers, blogs) — cite them inline.
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## Repository structure
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```
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ghaymah-genai-exam/
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├── README.md ← you are here
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├── common-qabilah/
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│ └── qabilah-ecosystem.md ← task + answer template
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├── common-mortakaz/
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│ └── mortakaz-discovery.md ← task + answer template
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├── q1-cumin-memory/
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│ └── cumin-memory-module.md ← task + answer template
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├── q2-arabic-tts-stt/
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│ └── arabic-tts-stt-proposal.md ← task + answer template
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├── q3-ghaymah-signup/
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│ └── ghaymah-signup.md ← task + answer template
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├── q4-static-site-deploy/
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│ ├── static-site-deploy.md ← task + answer template
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│ └── site/
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│ ├── index.html
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│ └── style.css
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└── q5-llm-agent/
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├── llm-agent.md ← task + answer template
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├── agent.py ← starter LangChain agent
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└── requirements.txt
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```
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## How to submit (GitPasha)
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1. Answer every question by editing the template files in place.
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2. Commit as you go, not one big dump at the end:
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```bash
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git add . && git commit -m "q1: memory module design"
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```
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3. `git push origin main` when done.
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4. Verify on GitPasha that every file (including your Q4 site source and Q5 code) is present.
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## Scoring rubric
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| Question | Weight | What “excellent” looks like |
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| common-qabilah | 5% | Real profile URL |
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| common-mortakaz | 15% | Two concrete products, technically-grounded integration with Ghaymah's AI stack, honest challenges |
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| Q1 memory module | 25% | Clear memory taxonomy, concrete storage choices, sensible write/read policy, runnable pseudocode, Ghaymah integration |
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| Q2 TTS/STT | 15% | A well-justified model + dataset with correct Arabic specifics (dialect, diacritization, license) |
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| Q3 signup | 5% | Confirmed signup + thoughtful platform observations |
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| Q4 static site | 15% | A live URL that resolves + source committed + a short write-up |
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| Q5 LangChain agent | 20% | A working agent wired to Ghaymah's LLM endpoint, with at least one tool and clear code |
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---
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Good luck — and welcome to the tribe. 🐪
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