AI Engineering

Build and operate AI systems.

Role-based pathways for engineers moving from product development into customer delivery, agent systems, model development, and production AI.

What this pathway developsThe ability to design, build, evaluate, and operate complete AI systems.

How to choose

Choose the part of an AI system you want to own.

Start from the role and responsibility, not the current tool. Each pathway builds a different part of the production AI lifecycle.

Programs

Explore each engineering pathway.

Open a programme to compare its scope, expected foundation, representative system, and practical outcome.

AI Engineer

Build production AI products end to end: LLM APIs, retrieval, agents and tool use, evaluation, guardrails, tracing, and deployment. Become an AI engineer who can also work forward-deployed.

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Designed forSoftware engineers and technical builders moving into AI engineering roles.

Recommended foundationBasic coding experience is useful. Programming foundations are included, so you can build the basics and start using tools at your own comfort.

Product interfacesLLM APIsPrompt and context engineeringEmbeddings and retrievalAgents, tools, and memoryEvaluation

Practical outcome

A deployed AI product with retrieval, agents and tool use, evaluations, guardrails, and operational traces.

View current program

System mapA production AI system

Product interface

LLM + orchestration

Embeddings + retrieval

Agents, tools + memory

Guardrails

Evaluation + tracing

Deployment

Across every pathway

Learn the system through working software.

01Understand the system

Learn the interfaces, data, models, controls, and infrastructure behind the capability.

02Build working components

Turn concepts into services, integrations, evaluations, and deployable systems.

03Develop engineering judgment

Make trade-offs, investigate failures, and explain why the system behaves as it does.