IRIS is in the middle of a step-change in how we build software.

Our Agentic SDLC programme is moving the organisation from tool-assisted engineering to agentic as the default way of working, with a 3x productivity target for FY27. As coding velocity rises, the constraints on quality shift. Manual testing as the dominant model no longer fits and the legacy assumption that parts of our estate "cannot be automated" is being actively disproved by modern AI-assisted tooling.

We're looking for an exceptional Quality Engineering leader to define and drive what quality engineering looks like at IRIS in this new world.

This is a strategic transformation role first, and a delivery role second. You'll set the vision, establish standards, lead organisational change, and build the quality engineering model that supports the next generation of software delivery at IRIS.

The destination is clear: smaller, more specialist quality engineering functions, confident in automation, embedded in pods, owning curated end-to-end capability per product, and over time extending into performance, resilience, and chaos engineering.

Importantly, this is a quality strategy, not a cost exercise. Our focus is on better product quality, faster feedback loops, lower defect leakage, and creating a quality function whose impact compounds rather than scales linearly with engineering output.

What You'll Be Doing:

Quality Engineering Strategy & Transformation

You'll own the global quality engineering strategy across all five Product & Engineering divisions and define the destination model for Quality Engineering across IRIS.

Key responsibilities include:

• Own the global quality engineering strategy across all five P&E divisions, including the destination model for the QE function and the transition path to it.
• Lead the automation maturity assessment across the estate — baseline current state, including the legacy and on-prem portfolio, and build the evidence base for subsequent decisions.
• Support defining and transitioning to the right Eng:QA ratio by pod archetype and divisional context.
• Define and own the standards for automated testing across the toolchain: unit, integration, contract, E2E, and AI-generated test coverage. Integrate with the standard PDLC and the agentic workflows being rolled out.
• Establish the curated E2E capability suite per product line, what is owned centrally, what sits in pods, and how it is maintained.
• Partner with the Director of Agentic SDLC on the QE-specific elements of bootcamp cohorts, agentic workflows for test generation, and the upskilling pathway for manual testers moving toward automation engineering.
• Provide the evidence and framing the divisional VPs need to lead the QE workforce conversation in their divisions, supporting the destination model, the upskilling pathway, and the honest position on roles that cannot make the transition.
• Support the small specialist Quality Engineering practice that can carry the standards, tooling choices, and harder testing problems that don't belong in any single pod.