Platform Software Engineer

The Storage Engineering team builds and operates the storage products used across G-Research. As a Platform Software Engineer, you'll build the APIs, workflows and data models that turn manually operated infrastructure into self-service products. The work includes capacity requests, tenant and quota automation, reporting and data lifecycle services. You'll make infrastructure changes safe, repeatable and auditable, while keeping observed state separate from intended change. This is a software engineering role within an infrastructure team, working alongside colleagues responsible for security, research infrastructure and developer platform services. Storage experience is useful but not required. You'll operate the services you build and join the team's out-of-hours on-call rotation. Key responsibilities of the role include: Building and operating services and APIs in Python, Go and TypeScript Automating capacity, tenant, quota, access and data lifecycle workflows Building self-service requests with explicit policy checks and exception paths Modelling infrastructure state and making changes idempotent, attributable and auditable Defining stable contracts between storage platform and developer platform services Building tests, fixtures and observability that make failures safe to diagnose Working with users and partner teams to turn operational problems into bounded engineering work Participating in incident response and the out-of-hours on-call rotation

Requirements

The ideal candidate will have the following skills and experience: Strong Python, with practical Go and TypeScript software engineering skills Experience designing, testing and operating APIs and backend services Strong use of coding agents in day-to-day delivery, with clear task boundaries, careful review and tests controlling the output. Experience building infrastructure automation, workflows or reconciliation systems Understanding of retries, partial failure, concurrency, idempotency and eventual consistency Strong Linux and production troubleshooting skills Experience with CI/CD, observability and safe deployment practices A practical approach to security, permissions, audit and change control A calm, methodical approach to incidents Desirable experience includes orchestration, configuration management, enterprise identity and data lifecycle tooling. Storage experience is useful but not required; strong platform software engineering skills and adaptability are more important. We expect every colleague to actively bring AI into their daily workflow to deliver impact.