Senior Full Stack Engineer, IG Group

• This role suits engineers with a strong grounding in software engineering practice: test-driven development, pair programming, and real ownership of systems from design through to production support, with real depth in Java and the modern backend services ecosystem
• The fundamentals matter most: engineers who can write their own tests, review their own designs, and catch their own defects, and who use AI to extend that practice further and faster. Growing into the person the whole group comes to for technical judgement is part of the role
• Extensive background as a Software Engineer, with demonstrated technical judgement on production systems
• We'll consider those stronger in front end React / React Native or hands-on expertise in Java or a comparable backend service ecosystem - as long as you have experience in and are happy working across the stack
• Strong fluency in test-driven development and pair programming as working disciplines
• Real ownership experience: you’ve designed features or systems, built them, deployed them, and supported them in production
• A genuine appetite for aggressive automation. You get energised by removing manual steps entirely
• Some experience evaluating or using LLM-based developer tools in a real engineering environment

Desirable

• We’re looking for a Senior Full Stack Engineer to push hard on AI across Lifecycle engineering: AI-assisted coding, testing and deployments, defect triage and observability, and the internal tooling that connects our AI tools safely to Jira, GitLab, and our CI/CD pipeline. This is a hands-on role on our Java backend. You’ll build tooling yourself, and you’ll help set how your team adopts it
• The long-term goal is a pipeline where AI agents handle the bulk of coding support, testing, and triage end-to-end, largely unattended, with engineers stepping in for genuine judgement calls and exceptions. We’re early on that path today, and we want someone in this role who treats the destination as real and pushes their team toward it deliberately
• Build and maintain internal tooling that embeds AI into day-to-day engineering work: coding assistants, AI-assisted test generation, deployments, and defect triage
• Contribute to observability in the AI-assisted pipeline, so every stage shows what the tooling is doing, catching, and missing
• Identify manual steps in coding, testing, and release that can run largely unattended, and help build the automation to get there
• Split work into small, releasable pieces that ship continuously
• Work closely with a product person on your product domain, so what you build is grounded in real delivery
• Treat improving ways of working and driving AI adoption as a fundamental, ongoing part of delivering value
• Work with the test and PM function to bring AI into the testing pipeline: exploratory test generation, defect clustering, flaky-test detection, and smarter prioritisation of what to test
• Evaluate and help roll out LLM-based developer tools, for example Claude Code and similar, integrating them safely with our Jira, Confluence, and GitLab environments
• Follow and help refine standards for responsible AI use in the SDLC: data handling, prompt hygiene, and guardrails around production and customer data
• Mentor less experienced engineers on effective use of AI tooling
• Work with security and compliance to make sure AI tooling meets IG’s regulatory and data-handling requirements
• Track the metrics that show whether AI tooling is helping: cycle time, defect escape rate, test coverage, delivery turnaround. Iterate based on what the data shows

• End Date: October 31, 2026