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Trading companies build bespoke hardware stacks and have larger platform engineering teams than most workplaces. For software engineers, it's a lucrative niche in terms of compensation, full-stack work, and engineering challenges. Software engineers tend to know little about trading companies. This post covers in depth how engineering works in a modern trading business.

Nvidia announced financing platforms with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR, aiming to raise over $500 billion in outside capital for AI "factories," the data centers that train and run AI models, with Jensen Huang pitching this compute as a durable, reusable "investable asset class." The core problem is that these are non-binding MOUs, not signed deals, and the entire pitch hinges on residual value, what the hardware is actually worth if the paying customer walks away, since Huang's own evidence for durability (rising H100 rental rates) proves current earnings, not resale value.

Beelzebub provides a platform that traps attackers already inside a network, using LLM-based decoys, continuous emulation, and an AI analyst to generate incident reports. It runs on-premises or as SaaS and pulls threat feeds from 60+ researchers.