Platform Engineer - AI and Internal Tooling

Job description

About Gattaca Gattaca is an engineering-driven crypto technology company based in London. We build and operate Titan, the largest block builder on Ethereum. We are venture backed and have been profitable for the past 3 years. Blockchains have created something genuinely new: a trustless, shared layer for financial instruments. For that to work at scale, the network needs infrastructure that can support extremely high throughput and sophisticated trading, while keeping the underlying system decentralised. That's what we build. Ultra-performant infrastructure that keeps decentralised networks efficient. The role This role exists to increase the operating leverage of Gattaca’s engineering team. You’ll sit within the Platform team and focus on the tools and systems around how we build software, operate production and access information internally. Some of that will be traditional developer tooling. Increasingly, a lot of it will involve finding useful ways to apply AI to workflows that previously required an engineer sitting in front of a terminal. There is a surprising amount of leverage available here. Our systems generate terabytes of data and our engineers can inspect almost every part of what happens inside them, but getting to that information often still requires knowing which database to query, dashboard to open or machine to inspect. The same is true of engineering workflows: useful context is spread across code, production systems, internal messaging, incident notes and individual engineers. We want to make all of that much easier to use. The job is to work out where better tooling can remove meaningful friction, then build it properly. Sometimes that will mean a simple internal application. Sometimes it will mean using AI to review code, investigate production issues, query internal data or automate repetitive engineering work. What you’d work on Your day-to-day work will span these main areas: AI-assisted engineering We want to use AI where it actually improves how we build and operate software. Code review is an obvious example, but there is much more scope around debugging, investigation, repository workflows and repetitive engineering work. A large part of this role will be working out where those systems are genuinely useful, choosing the right models and tools for the job, and building the infrastructure around them so they become part of norma…