Software Engineer (AI-Native)

Accepting applications until:

27 November 2026

The Commercial Technology team develop and maintain the products that drive the commercial revenues at Global for both the Radio and Outdoor parts of the business.

You’ll work across a suite of microservices — some event-driven — and own them through their whole lifecycle: design, build, CI/CD (Jenkins / Terraform), running them on Kubernetes (EKS on AWS), and keeping them healthy in production (Prometheus / Grafana). Much of our estate is Java 21 and Spring Boot, but we care more about how you design, reason about and operate systems than about which language you write them in.

We embrace modern AI coding tools in our daily workflow. With AI writing more of the code, the engineering judgment around it matters more than ever: we want engineers who can orchestrate AI at the level of design and specification, not just code faster with it.

We are a friendly, close-knit team working in a highly collaborative, agile environment.

• Design and deliver features, making sound architectural decisions that support the roadmap, not just the next ticket.
• Own services in production: instrument them well, understand how they behave under load, and diagnose issues when they don’t.
• Collaborate with engineers, architects and product owners to shape requirements and weigh up trade-offs.
• Raise the engineering bar through reviews of human- and AI-written code, covering correctness, security, performance and maintainability.

What You Might Work On

• Growing AdPower, our new self-service platform. AdPower lets advertisers plan, book and run campaigns themselves. You’d help scale it as more customers and more volume come through: new features, the event-driven integrations behind them, and keeping it fast and reliable as usage grows.
• International rollout for Outdoor. You’d take our Outdoor products into new markets, which means supporting multiple currencies, time zones, local inventory and regional rules. You’d also help decide what should be shared across markets and what needs to be configured per market.
• Accelerating IT transformation. Replace legacy systems and manual processes with modern, reliable services. That gets new commercial products to market faster, protects revenue from outages, cuts the cost to run and gives the business better data.
• AI enablement and our software factory. You’d help build the tools and workflows that let AI agents take a feature from specification to production safely. That includes guardrails, review and testing standards, and reusable skills and patterns for the rest of the team.
• Shipped production features using AI tools effectively, without compromising quality.
• Diagnosed a real production issue using our logs, metrics and traces.
• Contributed to design discussions and team practices — AI workflows, observability or security.
• Built a solid understanding of the business context and our system architecture.

• System design & architecture — Experience designing distributed services and APIs; you can explain the trade-offs behind your choices (sync vs async, consistency, failure modes, scaling) and when not to add complexity.
• Observability — You instrument what you build and know how to use it. Given a slow endpoint, you can trace it through metrics, logs and distributed traces to the real cause.
• Performance & caching judgment — You know when caching helps, when it doesn’t, and what it costs (invalidation, staleness, consistency).
• Security — A working grasp of secure design: authentication and authorisation, secrets handling, input validation and common vulnerabilities (e.g. OWASP Top 10).
• Engineering fundamentals — Strong grasp of design patterns, clean code and SOLID principles, with a habit of writing well-tested code.
• Backend development — Solid commercial experience in a modern backend language, plus relational and NoSQL persistence and messaging such as Kafka or SNS/SQS. Java / Spring Boot experience is preferred, but we welcome strong engineers from other languages who are keen to pick up our stack.
• AI-native development — Hands-on use of AI coding assistants (Claude Code, Copilot, Cursor or similar), with the judgment to know when to lean on them and the rigour to review what they produce.

Think big – Strive to do what hasn’t been done before

Own it – Take pride in what you do and do it well

Keep it simple – Keep it simple to get stuff done

Better together – We’re team players