Why LLM Engineering Is a Cloud Security Problem Nobody Is Talking About

Everyone wants to be an LLM engineer right now.

And I get it. The space is moving fast and the opportunities are real.

But here is what most people getting into it are skipping.

LLMs are powerful. They are also unpredictable; expensive to run and surprisingly easy to break if your infrastructure is not solid underneath them.

Prompt injection is real. If your application takes user input and passes it directly to a model without sanitization; you have already built a vulnerability. Not a bug. A vulnerability.

Your API keys are sitting in environment variables. Your model endpoints have no rate limiting. Your logs are capturing sensitive user inputs. Your cost per token is scaling faster than your revenue.

These are not AI problems. These are cloud security and engineering problems that happen to live inside an AI product.

The best LLM engineers I have seen are not just good at prompting. They understand IAM; secrets management; rate limiting; observability and cost controls. They treat the model like any other production service.

Because it is.

If you are building with LLMs and not thinking about security; you are not building a product. You are building a liability.

Secure the infrastructure first. Then ship the intelligence.