#Tunisia AI Development Bootcamp Instructor

GOMYCODE | AI Development Instructor

GOMYCODE is looking for a passionate and experienced AI Development Instructor to deliver our AI Development Bootcamp — helping learners build practical AI and software development skills across an intensive, project-based journey.

• Position: AI Development Instructor · 
• Engagement: Part-time · 
• Location: Remote + Physical Hackerspaces
•  Availability: Immediately

About the Bootcamp

• Our 280-hour AI Development Bootcamp takes learners from programming fundamentals to building and deploying production-grade AI applications. Over 5.5 months, each cohort builds a real product end-to-end — from first HTML page to a containerized, monitored LLM service — culminating in a portfolio-ready capstone and final defense. It's designed for learners transitioning into AI-related careers.

Your Responsibilities

• Deliver engaging, hands-on training sessions with live coding rather than slide-driven lectures
• Lead workshops, project checkpoints, and one-to-one sessions with blocked learners
• Explain technical concepts clearly to a mixed-ability cohort, pacing across a 5.5-month arc
• Guide learners through the build and help them debug alongside them, not for them
• Review learners' code and deliverables and give specific, constructive feedback
• Encourage problem-solving, self-learning, and sound development practices
• Support learners through final project completion, documentation, and presentation
• Prepare learners for the job market: portfolio review, GitHub profile, technical interview practice
• Stay current with AI and software development trends and fold them into delivery

Requirements

Professional background

• 3+ years shipping software professionally, including at least 1 year on LLM-powered applications in production — not prototypes only
• Experience taking an AI feature from idea to deployed, monitored service, with real exposure to its failure modes: latency, cost, rate limits, hallucination
• Portfolio evidence: GitHub, deployed applications, technical writing, or talks

Python & backend

• Advanced Python: data structures, functions, file handling, error handling, virtual environments
• FastAPI in production: endpoint design, Pydantic validation, error handling, Swagger/OpenAPI
• Databases & auth: persistence, registration/login flows, JWT, protected routes
• Async & performance: async/await, background tasks, timeouts, retries, caching, streaming
• Testing: pytest, httpx, curl

Frontend fundamentals

• HTML5, CSS (box model, responsive design), Bootstrap
• JavaScript: ES6, DOM manipulation, events, form validation, fetch
• Able to explain the browser–server request cycle to a complete beginner

LLM integration & AI engineering

• Core concepts, teachable not just usable: tokens, context windows, inference, model settings, cost/latency trade-offs, open-weight vs. closed models
• OpenAI SDK and Mistral AI: mistralai SDK, model family selection, OpenAI-compatible endpoint, mistral-embed, data sovereignty; provider-agnostic architecture
• Prompt engineering & structured outputs: system prompt design, JSON output, parsing
• LangChain: chains, chat history, document extraction
• Agents & RAG: tool calling, MCP tool servers, embeddings, chunking, vector search, retrieval-augmented generation
• Guardrails & evaluation: prompt injection defense, PII handling, bias awareness, LLM output testing

DevOps & deployment

• Git/GitHub: branching, pull requests, code review, repository hygiene
• Docker: containerizing a Python API
• Linux: command line, environment and secrets management
• CI/CD and AWS basics: automated testing pipelines, deploying a containerized service
• Monitoring: logging, error tracking, LLM usage and cost visibility
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AI-assisted development & automation

• Responsible use of GitHub Copilot, Copilot CLI and Claude Code — including reviewing and rejecting AI-generated code
• Zapier and n8n: workflow building, webhooks, connecting automations to a custom API

Languages

Fluent in  French 

Nice to Have

• Previous experience as a trainer, instructor, mentor, or technical coach — particularly mentoring capstone projects through to defense
• Experience working on real-world AI projects beyond internal tooling
• Deeper cloud, deployment or DevOps background (infrastructure-as-code, multi-service architectures)
• Experience supporting career changers and first-time developers
• Open-source contributions or an active technical publishing presence
  
  

What We Offer

• The opportunity to teach and mentor the next generation of AI professionals
• A dynamic, innovative learning environment built on a practical, project-based approach
• Hands-on work with modern AI technologies and a curriculum kept current with the field
• Full curriculum, session materials, and program management support so you can focus on teaching
• A direct, visible contribution to learners' career outcomes

How to Apply

If you are passionate about AI, technology, and education, submit your CV and GitHub profile to [email]. Please include a short note (5–10 lines) on an LLM application you've built and what broke in production.

Informations

Exigences

Compétences:

AI DEVELOPPEMENT API development