Engineers and engineering leaders who build, deploy, and scale software systems.

Applying AI tools and techniques to professional workflows — assign alongside more specific AI topics.

Building autonomous AI agent systems that take actions, use tools, and orchestrate multi-step workflows.

Using AI coding assistants and tools to write, review, and ship code faster.

Designing scalable, reliable software systems — architecture patterns, distributed systems, and technical tradeoffs.

Measuring and evaluating AI model performance, quality, and reliability for production use cases.

Designing and optimizing the context window for LLM applications — prompt structure, memory, and information retrieval.

Operating and deploying large language models in production — fine-tuning, inference, monitoring, and cost optimization.

Building retrieval-augmented generation and search systems — vector databases, embeddings, ranking, and retrieval pipelines.

Learn how to build, deploy, and scale AI agents on GCP

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