AI Engineering Instructor at Ayonaire Academy

𝗝𝗢𝗕 𝗗𝗘𝗦𝗖𝗥𝗜𝗣𝗧𝗜𝗢𝗡 — 𝗔𝗜/ML 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗜𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗼𝗿 𝗮𝘁 𝗔𝘆𝗼𝗻𝗮𝗶𝗿𝗲 𝗔𝗰𝗮𝗱𝗲𝗺𝘆

Ayonaire Academy is an edtech company on a mission to help students land global jobs and opportunities through global skills and mentorship.

We're not just teaching skills, we're building the #1 tech school in Africa, modeled after Harvard Business School, where quality of education comes before institutional reputation. Our culture is excellence.

Our values are excellence and the quality of education we deliver.

The Opportunity
We are hiring an AI Engineering Instructor to teach our 10-month, 3-Act AI Engineering Program from complete beginner through Python foundations, into core machine learning and deep learning, and all the way to modern AI engineering (RAG, LangChain, LangGraph, agentic AI, and MCP). Classes hold 3 times a week.

Our teaching approach is intentional and different from typical tutorial-style learning. We break down complex topics even ones like transformers, backpropagation, or multi-agent systems into simple, digestible parts so students genuinely understand and apply what they learn, not just follow along. Every class is built around a real-world problem statement, and every module ends in a portfolio-worthy project.

This is not a "watch and repeat" teaching role, this is ownership of how students actually become AI Engineers.

What You'll Own:

1. 𝗖𝘂𝗿𝗿𝗶𝗰𝘂𝗹𝘂𝗺 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝘆 𝗔𝗰𝗿𝗼𝘀𝘀 𝘁𝗵𝗲 𝗙𝘂𝗹𝗹 𝗣𝗿𝗼𝗴𝗿𝗮𝗺
   
   • Teach across Act 1 (Python Fundamentals, NumPy, Pandas, SQL/NoSQL, Statistics, EDA, Streamlit, Git), Act 2 (ML, Ensemble methods, Deep Learning, NLP, Computer Vision, MLOps, Cloud deployment), and Act 3 (GenAI, Vector Databases, RAG, Advanced RAG, LangChain, LangGraph, Agentic AI, MCP, Multi-Agent Systems)
   • Break down historically "intimidating" topics (the kind that make people want to run from AI Engineering) into simple, methodical, digestible parts
   • Structure every class around a real-world problem statement, not abstract theory
   • Deliver module projects exactly as scoped in the curriculum (e.g. Stock Price Analyser, Cancer Risk Prediction System, Tumour Classification, Policy Q&A Bot, Multi-Agent Research System) and hold students to the skill standard each project demands
   

2. 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗚𝗿𝗮𝗱𝗲, 𝗣𝗿𝗼𝗷𝗲𝗰𝘁-𝗕𝗮𝘀𝗲𝗱 𝗧𝗲𝗮𝗰𝗵𝗶𝗻𝗴
   
   • Teach using a real development workflow (VS Code), not Jupyter notebooks or Google Colab
   • Guide students through end-to-end, production-grade projects no toy datasets, no notebook-only demos
   • Teach clean code structure, Git/GitHub version control, Docker containerization, CI/CD with GitHub Actions, MLflow/DVC experiment tracking, and cloud deployment (AWS/Azure)
   • Help students build systems the way real companies build systems — full architecture, not just models
   

3. 𝗦𝘁𝘂𝗱𝗲𝗻𝘁 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 & 𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱𝘀
   
   • Give assignments, Quiz and Classwork after every class to reinforce learning and push independent building
   • Hold students to a standard of proof of competence through shipped systems, not just attendance
   • Move students from "course learners" to professionals who can confidently design, build, and deploy real AI solutions including modern GenAI/agentic systems
   • Provide clear, constructive feedback that helps students genuinely improve, not just pass
   

What We're Looking For — Required

• Strong hands-on experience in AI/ML engineering — Python, ML, Deep Learning, NLP, Computer Vision, GenAI, RAG, or Agentic AI
• Proven ability to teach or explain complex technical concepts in a simple, structured, methodical way
• Strong communication skills — able to hold attention and make difficult topics feel approachable
• Experience with real-world, production-level workflows: Git, Docker, CI/CD, MLOps, cloud deployment
• Comfortable teaching live, 3 times a week, with consistency and energy

Strong Plus — (Not Required)

• Prior teaching, mentoring, or instructional experience (bootcamps, Udemy, YouTube, workshops)
• Hands-on experience with LangChain, LangGraph, vector databases (ChromaDB, FAISS, Pinecone), or MCP
• Experience deploying ML/AI systems on AWS or Azure in a company setting

Who You'll Thrive As
You'll thrive here if you:

• Believe AI Engineering can be taught simply, without dumbing it down
• Care as much about how a student learns as what they learn
• Think in systems and real-world application, not isolated demos
• Are comfortable holding students to a high standard
• Want to help build one of Africa's most ambitious tech schools

Requirement to Apply Please record a short video teaching a simple topic (e.g. OOP or Functions) so we can see your teaching methodology in action.

How to Apply Send your CV, portfolio, and teaching video to [email protected]