Rust Systems Engineer - Distributed Storage & Kubernetes

Barlowe LLP; Greater London; On-site; GBP 110,000 - 160,000; Full time

Benefits offered by this job

Lunch provided

Barista bar

Monthly events

Job summary

G-Research in London is seeking a software engineer to join the Custom I/O team building a new distributed storage platform in Rust. You will work with researchers and engineers to shape how data is stored and accessed, helping to design a platform relied on by multiple teams.

Key responsibilities include designing core components in Rust, building scalable and resilient systems for large data workloads, and integrating Kubernetes and streaming technologies such as Kafka while maintaining

Qualifications

• Commercial experience developing production systems in Rust.
• Solid grounding in distributed systems and design trade-offs.
• Experience handling large data volumes reliably.
• Collaborative and able to explain technical decisions clearly.

Responsibilities

• Designing and developing core components of a distributed storage platform in Rust.
• Building scalable, resilient and performant systems for large data workloads.
• Collaborating with researchers and engineers to understand data access requirements.
• Contributing to architectural decisions across distributed systems and data management.
• Developing and optimising services that run in Kubernetes environments.
• Integrating event-driven and streaming technologies, including Kafka, into the platform.
• Promoting engineering best practices, code quality and testing.

Skills

Rust

Distributed systems

Data handling

Kubernetes

Kafka/Streaming

Communication

Testing/Quality

Tools

Kubernetes

Kafka

Job description

G-Research in London is seeking a software engineer to join the Custom I/O team building a new distributed storage platform in Rust. You will work with researchers and engineers to shape how data is stored and accessed, helping to design a platform relied on by multiple teams.

Key responsibilities include designing core components in Rust, building scalable and resilient systems for large data workloads, and integrating Kubernetes and streaming technologies such as Kafka while maintaining