Platform Software Engineer – DevSecOps & AI Tooling

We are hiring a DevSecOps Engineer to join our AI-first Developer Platform team. The team owns the CI/CD pipelines that every engineer here ships through. We also build our own products on top of GitHub, Artifactory, and a Kubernetes-hosted marketplace of build runners. This is a hands-on build role in a regulated environment. You will build working software, not documents. You will own products, tools, services and security from end to end, and what you ship reaches delivery teams the same week. We assess evidence over years. Show us what you have built, what you measured, and a decision the measurement changed.

Build working prototypes, and harden the ones that prove their value. Put agents to work on the toolchain, for example remediation at scale, pipeline upgrades, scanner triage and credential rotation. Design how autonomous agents are allowed to act. This includes identity, scoping, audit trail and a stop control. Create new products on our platform, such as self-serve dashboards, MCP servers, skills and developer tooling. Make the secure, correct path the default in the pipeline, so developers do not have to do more, earlier. Run time-boxed experiments, each with a decide-or-kill date and a written verdict. Make the estate observable, through monitoring, telemetry, logging, tracing and alerting. Talk to delivery teams directly, and bring back findings that change the roadmap. Help run the platform, using zero-downtime practices that are defined in code and tested before release.

Test-driven and behaviour-driven development as your default way of working, including for pipelines, infrastructure and agents. Practical DevSecOps, where teams own their pipelines and security is part of building. Trunk-based development, with short-lived branches. Pairing as a normal way of working. Infrastructure as code, reviewed and tested as code. Measuring a problem first, then testing each solution against that measurement. Real experience with observability, including monitoring, telemetry, logging, tracing and alerting. Experience driving delivery metrics toward elite DORA performance, and understanding that the system matters more than the number. Hands-on use of AI tools such as Claude and GitHub Copilot, and interest in how engineering changes in an AI-first world. Some experience with CI/CD platforms, patterns and practices, and genuine interest in where they are going next.

Experience with C#, Python or TypeScript. Experience with Terraform, AWS or Azure. Experience with GitHub, Azure DevOps or Artifactory. Product instinct: you ask who the user is and what they will adopt before you ask what is technically interesting. Experience teaching others through pairing, writing or speaking internally.