Quant Systems: Systems Developer (London) (4E5067B)

Referment; Greater London; On-site; GBP 70,000 - 100,000; Full time

Job summary

Referment is partnering with a global investment and technology organisation to hire a Systems Developer for a team responsible for high-performance research and trading infrastructure. This hands-on role spans large-scale compute, operating systems, development tooling, networking and storage.

You’ll design workload scheduling, fleet management, clustered file systems, and performance tuning of kernel and network stacks to support latency-sensitive workloads.

Qualifications

• Experience in infrastructure orchestration and fleet management.
• Advanced Python proficiency for systems engineering, including high-concurrency frameworks.
• Degree in Physics, Mathematics, Computer Science, or related technical field, or comparable practical experience up to five years.
• Curiosity about how complex technology works and the motivation to investigate unfamiliar problems.
• Clear written and verbal communication, organisation and time-management skills.

Responsibilities

• Design and improve workload scheduling and fleet-management capabilities for large compute environments.
• Contribute to clustered file-system design and operation, software lifecycle tooling and platform reliability.
• Investigate and tune kernel and network performance for latency-sensitive and high-throughput applications.
• Build metrics collection and analysis tools that help engineers understand and improve infrastructure behaviour.
• Collaborate with a global engineering team supporting research and trading workloads.

Skills

Infrastructure orchestration

Python

High-concurrency

Systems performance

Linux networking

Education

Physics/Math/CS degree

Tools

IaC (Ansible)

OCI/REST APIs

Job description

Referment is working with a global investment and technology organisation to hire a Systems Developer for a team responsible for high-performance research and trading infrastructure. This is a hands-on engineering role spanning large-scale compute, operating systems, development tooling, networking and storage.
You’ll work in a distributed computing environment where software engineering meets systems performance. The remit offers breadth across workload scheduling, fleet management, clustered file systems and the measurement and tuning of low-latency, high-throughput platforms.

The Role

• Design and improve workload scheduling and fleet-management capabilities for large compute environments.
• Contribute to clustered file-system design and operation, software lifecycle tooling and platform reliability.
• Investigate and tune kernel and network performance for latency-sensitive and high-throughput applications.
• Build metrics collection and analysis tools that help engineers understand and improve infrastructure behaviour.
• Collaborate with a global engineering team supporting research and trading workloads.

What We're Looking For

• Professional experience in infrastructure orchestration and fleet management is essential for this role.
• Advanced Python proficiency for systems engineering, including experience with high-concurrency frameworks (such as FastAPI or Asyncio) and the use of static analysis or type hinting.
• A degree in Physics, Mathematics, Computer Science, or a related technical field, or comparable practical experience of up to five years.
• Curiosity about how complex technology works and the motivation to investigate unfamiliar problems.
• Clear written and verbal communication, organisation and time-management skills.

Desirable Experience

• Experience with Infrastructure as Code (IaC) tools, with a particular interest in Ansible and the development of custom modules.
• Exposure to cloud-native infrastructure management and integration, such as OCI and REST APIs.
• Linux systems and networking.
• Exposure to HPC, storage, GPU infrastructure or data-centre hardware.

This could suit a software engineer, systems programmer or infrastructure developer looking to work close to the operating system and large-scale compute layer.
Referment