Rust Developer

Arcus Search; Greater London; On-site; GBP 129,000 - 185,000; Full time

Job summary

Arcus Search is seeking a Senior Rust Engineer to join a high-impact storage engineering team in London. You will design and implement core components of a greenfield distributed storage platform, focusing on scalability, performance, and reliability within a Kubernetes-based environment.

The role involves collaborating with quant researchers and infrastructure teams to shape architecture, drive best practices, and deliver a data-intensive platform that reduces reliance on third-party storage

Qualifications

• Commercial experience developing production systems in Rust (ideally 1–2+ years).
• Strong background building distributed systems and scalable backend platforms.
• Experience working with Kafka and event-driven architectures.
• Hands-on experience with Kubernetes and cloud-native technologies.

Responsibilities

• Design and develop core components of a greenfield distributed storage platform using Rust.
• Build highly scalable, resilient, and performant systems capable of handling large-scale data workloads.
• Collaborate with quantitative research and engineering teams to understand storage and data access requirements.
• Contribute to architectural decisions across distributed systems, data management, and platform scalability.
• Develop and optimise services running within Kubernetes-based environments.
• Integrate event-driven and streaming technologies, including Kafka, into the wider platform ecosystem.
• Drive engineering best practices, code quality, testing, and operational excellence.

Skills

Rust

Distributed systems

Kubernetes

Kafka

Performance optimization

Job description

Location:London (4 days onsite per week)Contract Length:12 Months (Initial Contract)Engagement:Inside IR35Rate:£700 - £1000 per day

Overview

We're partnering with a leading quantitative technology organisation to hire an experienced Senior Rust Engineer to join a high-impact Storage Engineering team. This is an opportunity to contribute to a strategically important, multi-year platform initiative focused on building a next-generation storage solution from the ground up.The team is developing a new distributed storage platform designed to provide greater scalability, performance, and operational control, reducing reliance on third-party storage technologies. An MVP has already been delivered, and the programme is now entering an exciting growth phase, with plans to expand the engineering team significantly over the coming months.Working closely with quant researchers, platform engineers, and infrastructure teams, you'll play a key role in shaping the architecture and engineering direction of a business-critical platform that sits at the heart of a highly data-intensive environment.

Key Responsibilities

• Design and develop core components of a greenfield distributed storage platform using Rust.
• Build highly scalable, resilient, and performant systems capable of handling large-scale data workloads.
• Collaborate with quantitative research and engineering teams to understand storage and data access requirements.
• Contribute to architectural decisions across distributed systems, data management, and platform scalability.
• Develop and optimise services running within Kubernetes-based environments.
• Integrate event-driven and streaming technologies, including Kafka, into the wider platform ecosystem.
• Drive engineering best practices, code quality, testing, and operational excellence.

Required Experience

• Commercial experience developing production systems in Rust (ideally 1-2+ years).
• Strong background building distributed systems and scalable backend platforms.
• Experience working with Kafka and event-driven architectures.
• Hands-on experience with Kubernetes and cloud-native technologies.
• Strong understanding of system design, performance optimisation, and reliability engineering.
• Experience working within highly technical engineering environments.

Desirable Experience

• Storage systems, data platforms, or infrastructure engineering experience.
• Experience building low-latency, high-throughput distributed applications.
• Exposure to quantitative, financial services, or data-intensive environments.
• Knowledge of large-scale data management and storage architectures.