Software Developer - Shared Engineering

• →Working primarily in Go, build and own platform services and internal tooling end-to-end, from design through to production. 
• →Improve developer experience by reducing friction in the build/CI/CD path, strengthen shared libraries. 
• →Help shape how the wider firm adopts AI/coding-assistant tooling safely and effectively, integrating it into workflows and building guardrails and tooling around it. 
• →Collaborate with the network and Linux engineers to understand what the infrastructure needs in order to scale and be managed, then expose it cleanly in software. 
• →Mentor and share knowledge, improving teammates' skills and making sure others can maintain and build on the systems you develop. 
• →Review and raise standards by thoughtful code review, sensible judgement on where to block versus where to let things flow, and a pragmatic sense of the right work to be doing right now. 
• →Take part in on-call once up-to-speed, troubleshooting problems that span several technical domains across current and legacy infrastructure. 
   

• Strong software-engineering fundamentals and production experience owning services end-to-end. Go is what you'd write day to day, but we care more about the fundamentals than the language: strong backgrounds in other statically typed languages are welcome. 
• Comfortable on Linux, with an understanding of the OS your software runs on (processes, networking basics, packaging, systemd), even if you're not a systems engineer. 
• Solid grasp of build systems, CI/CD, and release pipelines. You've worked in a monorepo or a serious build/release setup and made it better. 
• A track record of delivering: shipping, closing out, and not letting scope or polish stall a deliverable. 
• Good written and verbal communication, and the collaborative instinct to treat non-developer engineers as first-class colleagues. 
   

Desirable attributes

Things we'd like to see. You won't have all of them, and that's fine. 

• Interest or hands-on experience in developer experience and AI/coding-assistant tooling. Building or integrating LLMs into a real engineering workflow is a plus, but curiosity about how these tools change work practices counts too. 
• Experience with infrastructure/platform software: inventory/asset systems, monitoring, alerting, scheduling, container orchestration or similar backend platform work. 
• APIs, data pipelines and schema management: designing clean service APIs and moving data between systems reliably. 
• Infrastructure-as-code and cloud fluency. We use Terraform and AWS as required, but experience with Azure or GCP is just as relevant. 
• Exposure to server or network hardware, networking concepts, or datacentre operations.