Required Skills & Qualifications
- 10+ years of experience in AI/ML, Data Science, Generative AI, or Data Engineering roles.
- Strong experience in technical training, facilitation, or enablement for engineers, consultants, or enterprise teams.
- Proven ability to translate complex AI concepts into practical, hands‑on learning experiences.
- Excellent communication, storytelling, and stakeholder‑engagement skills.
Applied AI Skills & Technical Expertise
Core AI & GenAI
- Machine Learning pipelines, model evaluation, and deployment
- Generative AI, LLMs, prompt engineering, and solution design
- Retrieval‑Augmented Generation (RAG), agents, orchestration patterns
- AI ethics, responsible AI, and enterprise adoption considerations
AI Platforms & Ecosystems (Expertise in one necessary)
- Microsoft Ecosystem: Azure AI, Azure OpenAI, Azure ML, Copilot stack
- Google Ecosystem: Vertex AI, Gemini models, BigQuery ML
- AWS Ecosystem: SageMaker, Bedrock, AI/ML services
- Open‑Source Ecosystem: PyTorch, TensorFlow, Hugging Face, LangChain, Llama, OpenClaw
Data & Engineering
- Data engineering concepts, feature stores, MLOps / LLMOps
- Cloud‑native architectures and scalable AI solution design
Preferred Qualifications
- AI/ML, Cloud, or Technical Training certifications.
- Prior experience in consulting or client‑facing delivery environments.
