The Firm
XTX Markets is a leading algorithmic trading firm which uses state-of-the-art machine learning technology to produce price forecasts for over 53,000 financial instruments across equities, fixed income, currencies, commodities and crypto. It uses those forecasts to trade on exchanges and alternative trading venues, and to offer differentiated liquidity directly to clients worldwide. The firm trades over $250bn a day across 35 countries and has over 300 employees based in London, Singapore, New York, Paris, Bristol, Mumbai, Yerevan and Kajaani. We leverage the talent of the people who work here, modern computational techniques and state-of-the-art research infrastructure to analyse large data sets across markets quickly and efficiently, to maximize the effectiveness of our proprietary trading algorithms. We are actively seeking new methods and ideas. The models that drive our trading strategies have evolved considerably over the last 10 years, from econometric methods that gave our company its name, to trees, to neural networks, to modern deep learning architectures. XTX Markets has an unrivalled level of computational resources in the trading industry, with a growing research cluster currently containing well over 25,000 GPUs with more than 1 exabyte of usable storage. Teams across the firm include world-class researchers, developers and technologists with backgrounds in pure math, programming, physics, computer science and machine learning. The firm is also constructing a large-scale data centre in Finland to future-proof its significant computational capabilities. At XTX Markets technology is our business and we are a diverse organization which attracts outstanding talent from across all industry backgrounds. We are focused on teamwork and our people collaborate on all aspects of the business, working openly and with respect for each other, our clients and the market. Our culture is non-hierarchical and one where everyone is valued. We strive for excellence in everything we do.
The Role
- Working primarily in Go, build and own platform services and internal tooling end-to-end, from design through to production.
- Improve developer experience by reducing friction in the build/CI/CD path, strengthen shared libraries.
- Help shape how the wider firm adopts AI/coding-assistant tooling safely and effectively, integrating it into workflows and building guardrails and tooling around it.
- Collaborate with the network and Linux engineers to understand what the infrastructure needs in order to scale and be managed, then expose it cleanly in software.
- Mentor and share knowledge, improving teammates' skills and making sure others can maintain and build on the systems you develop.
- Review and raise standards by thoughtful code review, sensible judgement on where to block versus where to let things flow, and a pragmatic sense of the right work to be doing right now.
- Take part in on-call once up-to-speed, troubleshooting problems that span several technical domains across current and legacy infrastructure.
Essential attributes
- Strong software-engineering fundamentals and production experience owning services end-to-end. Go is what you'd write day to day, but we care more about the fundamentals than the language: strong backgrounds in other statically typed languages are welcome.
- Comfortable on Linux, with an understanding of the OS your software runs on (processes, networking basics, packaging, systemd), even if you're not a systems engineer.
- Solid grasp of build systems, CI/CD, and release pipelines. You've worked in a monorepo or a serious build/release setup and made it better.
- A track record of delivering: shipping, closing out, and not letting scope or polish stall a deliverable.
- Good written and verbal communication, and the collaborative instinct to treat non-developer engineers as first-class colleagues.
Desirable attributes
Things we'd like to see. You won't have all of them, and that's fine.- Interest or hands-on experience in developer experience and AI/coding-assistant tooling. Building or integrating LLMs into a real engineering workflow is a plus, but curiosity about how these tools change work practices counts too.
- Experience with infrastructure/platform software: inventory/asset systems, monitoring, alerting, scheduling, container orchestration or similar backend platform work.
- APIs, data pipelines and schema management: designing clean service APIs and moving data between systems reliably.
- Infrastructure-as-code and cloud fluency. We use Terraform and AWS as required, but experience with Azure or GCP is just as relevant.
- Exposure to server or network hardware, networking concepts, or datacentre operations.
Vacancy posted 11 days ago
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