Summary: Join Trade Me's SEO Platform team to build and improve the technical infrastructure for organic search, focusing on evolving search engines and AI-assisted development. Highlights: 1. Shape and contribute to defining the work that gets built 2. Hands-on engineering in an agile, squad-based model 3. Innovate with AI coding tools and LLM-based search evolution At Trade Me, we're about connecting Kiwi to create the life they want. Whether it's the big things like finding a home, a job, a car or growing their business, or the smaller things, like finding that right bedside table or parting ways with some old stuff. At Trade Me our vision is to be the place where Kiwi look first. This role sits at the centre of how Trade Me stays discoverable, not just to Google's traditional crawler, but to the LLM-based search engines that are reshaping how people find information online. The SEO Platform team owns the technical infrastructure behind millions of listings: structured data, URL management, sitemaps, server-side rendering, crawler behaviour, and page performance. In 2026, that means thinking about both classical SEO and how systems like Google AI Overviews, Perplexity, and ChatGPT Search consume and rank content differently. This is hands-on engineering work, delivered in an agile squad-based model. **What you'll do:** * Contribute to defining, estimating, and refining squad work; you're an active participant in shaping what gets built, not just how * Write production-quality code and unit tests across our full stack (primarily C#/.NET and TypeScript/Angular), with an emphasis on reliability, maintainability and performance * Peer review code with real scrutiny including AI-generated code with an eye for correctness, security and architectural fit * Build and improve the infrastructure that drives organic search performance: structured data pipelines, sitemap generation, server-side rendering, crawl behaviour and Core Web Vitals * Use AI coding tools effectively in your day-to-day workflow and know when to override them * Communicate your work clearly in documentation, code review and cross-functional conversations with other team members **What success will look like:** * You ship solutions that measurably improve organic search performance with before/after evidence you can point to * Your code maintains or improves the quality and performance of our technical platforms * You work autonomously while knowing when to collaborate or escalate * You evaluate AI-generated output critically, accepting, adapting or rejecting it based on quality and architectural fit * You keep pace with how LLM-based search is evolving and bring that understanding into how you build * Your squad and stakeholders have the information they need to make sound decisions **What you will bring to our team:** **Technical experience:** * 3+ years in professional software development, with evidence of shipping features to production in a team environment * Strong JavaScript/TypeScript experience; backend experience in C#/.NET, Java, Node.js, Go, or Python (adjacent stacks are welcome - ramp-up in an AI-assisted environment is faster than it used to be) * Experience with a modern frontend framework; Angular, React or Vue, at production depth * Solid understanding of relational databases and SQL, particularly Microsoft SQL Server * Familiarity with OO design patterns, SOLID principles, and what testable, maintainable code looks like in a long-lived codebase **SEO and performance:** * Some experience with technical SEO; structured data, sitemaps, server-side rendering for crawlers, Core Web Vitals, canonical URLs or a strong appetite to develop it * Awareness of how LLM-based search engines consume content differently from traditional crawlers is a meaningful differentiator * Demonstrated interest in web performance: you know how to measure it, and you've improved it **AI capability:** * You use AI coding tools (Copilot, Cursor, Claude Code, or similar) as a genuine part of how you work, not as a novelty, and not uncritically * You can evaluate AI-generated code for correctness, security implications, and architectural fit. Knowing when to reject AI output matters as much as knowing how to use it * Experience integrating LLMs or building AI-assisted features in a production context is a strong advantage; describe what you built, not just the tools you used **Ways of working:** * Collaborative and positive - a team player who makes the people around them better * Organised and comfortable with self-directed work in a fast-moving environment * Precise: you care about the details that make a web experience faster, more reliable, and easier to maintain