AI Engineer

What the job involves

• Design and ship retrieval-augmented generation (RAG) pipelines over company data
• Choose models and tune inference controls for cost, latency and reliability
• Defend against prompt injection and unsafe output before anything reaches users
• Evaluate AI features with real test sets rather than impressions
• Integrate model APIs into existing products and own them in production

Skills this role needs

These are the actual modules taught on the tracks that train for this role — not a generic skills list.

• AI Foundations — optional basics (free)
• Module 0 — Foundations: How AI Works & the GenAI Toolkit
• Foundations of Generative AI
• Large Language Models Deep Dive
• Prompt Engineering Mastery
• Building with LLM APIs
• Retrieval-Augmented Generation (RAG)
• AI Agents & Tool Use
• Fine-tuning & Embeddings
• Production AI Systems
• Context Engineering
• Modern LLM Architectures
• Voice & Multimodal Agents
• Module 0 — Foundations: Logic, Probability & Algorithms for AI
• AI Foundations
• Heuristic Search
• Adversarial Search
• Knowledge Representation
• Constraint Satisfaction
• Planning & Reasoning
• Probabilistic AI
• Reinforcement Learning

How to train for it