Distributed Systems Software Engineer- Leading Quantitative Trading Firms

eFinancialCareers; Greater London; On-site; GBP 200,000 - 500,000; Full time

Job summary

London-based opportunities in Quant Trading / Research Infrastructure require strong distributed systems experience and deep knowledge of concurrency and reliability. Engineers will work on large-scale compute, scheduling, and storage platforms, delivering low-latency, highly available systems for real-time data processing and research workloads.

Candidates should be proficient in C++, Java, Python, Go, or Rust, with a track record of building scalable infrastructure in demanding environments.

Qualifications

• Proven experience designing complex distributed systems.
• Strong software engineering fundamentals.
• Experience with high-performance, low-latency environments is a plus.

Responsibilities

• Design and develop large-scale distributed compute platforms.
• Build scheduling and workload orchestration components.
• Provide reliable, observable, high-performance research infrastructure.

Skills

Distributed systems

Concurrency

Reliability

Programming languages

Job description

London | £200k-£500k+ TC | Quant Trading / Research Infrastructure

Some of the most interesting distributed systems problems in technology aren't currently sitting inside traditional Big Tech.

I'm working with several leading quantitative trading firms building infrastructure operating at extraordinary levels of scale, throughput, latency and reliability.

Trading firms need to process global real-time data, run enormous research workloads, maintain highly available trading systems and provide researchers with access to vast amounts of compute. Current public material across the sector describes everything from distributed state-machine replication to simulations running across tens of thousands of compute cores.

Depending on the team, you could work on:

• Large-scale distributed compute
• Scheduling and workload orchestration
• Distributed storage and data platforms
• Real-time event-driven systems
• High-throughput messaging
• Fault tolerance and state replication
• Research infrastructure
• Petabyte-scale data
• HPC / CPU / GPU compute
• Observability and reliability
• Developer platforms and abstractions
• Performance engineering across compute, storage and networking

Looking for:

• Strong software engineering fundamentals
• Experience designing complex distributed systems
• Deep understanding of concurrency and parallelism
• Knowledge of reliability, consistency and failure modes
• Strong systems thinking
• Experience with C++, Java, Python, Go, Rust or similar

Prior trading experience is not required for many of these teams . The firms I represent are particularly interested in engineers from Big Tech, infrastructure companies, databases, cloud platforms, HPC, developer infrastructure and other technically demanding environments.

The key difference versus many large technology companies is proximity to impact : small teams, significant ownership, extremely capable colleagues and systems where improvements in performance or reliability can have an immediate measurable effect.

Whilst we carefully review all applications, to all jobs, due to the high volume of applications we receive it is not possible to respond to those who have not been successful.