Platform Engineer

Company Overview

A global technology-led organisation operating large-scale, data-intensive and computationally demanding systems. Engineering is central to the business, with significant investment in distributed computing, research infrastructure, and high-performance platforms.

Team

You will join a specialist platform engineering team responsible for building the infrastructure and services underpinning large-scale computational research.

Key Responsibilities

1. Design, build, and operate distributed services managing compute workloads and data access across large-scale infrastructure

2. Develop platform APIs and tooling to improve researcher and developer productivity

3. Improve the reliability, scalability, and performance of compute-intensive workflows

4. Build solutions across workload orchestration, resource management, observability, and security

5. Translate complex research and infrastructure requirements into scalable platform capabilities

6. Take end-to-end ownership from system design and implementation through to production operation

Required Experience

1. 8-12+ years building and operating large-scale distributed systems in production

2. Strong programming skills in C++, Java, Rust, Go , or similar systems languages

3. Strong understanding of distributed systems, concurrency, performance, reliability, and fault tolerance

4. Experience designing platforms, services, or infrastructure used by other engineers

5. Degree in Computer Science or a related technical discipline, or equivalent practical experience

Desirable Experience

1. Internal developer platforms, cloud infrastructure, orchestration systems, or HPC

2. GPU-accelerated computing and/or ML infrastructure

3. PyTorch, TensorFlow, or similar frameworks

4. Experience supporting researchers, data scientists, or highly technical engineering users

5. Large-scale, data-intensive or performance-sensitive environments

Why Join

1. Solve complex distributed systems and infrastructure problems at significant scale

2. Build platforms that directly accelerate computational research

3. Work on challenging problems across HPC, distributed computing, orchestration, and platform engineering

4. High degree of technical ownership and autonomy