About this role

You’re a strategic operator who loves turning complex engineering organisations into high-performing, data-driven machines. In this role, you will shape the operating rhythm for an 800-person global engineering org in a high-growth SaaS environment, using metrics, portfolio visibility and AI-enabled tooling to drive predictable, high-quality delivery at scale. You’ll sit at the intersection of strategy, data, delivery and culture, giving senior leaders the insight and frameworks they need to make better decisions, faster.

You’ll own engineering performance dashboards and success metrics, optimise workflows and tools (Jira, Confluence, GitHub, CI/CD), and lead cross-functional initiatives that span Product, Design, QA and Customer Success. You’ll also build and mentor a globally distributed team, influence senior stakeholders and embed continuous improvement across the organisation. If you’re excited by high visibility, broad scope and meaningful impact, keep reading.

Here’s a breakdown of what you’ll do Architect and own the engineering operating cadence (QBRs, monthly business reviews, strategic planning and org-wide communications) to drive clarity and alignment. Define and maintain engineering success metrics and performance dashboards, turning complex datasets into clear, actionable insights for senior leadership and the Board. Maintain a portfolio-level view of major engineering initiatives, flagging risks early and standardising delivery frameworks to improve predictability and quality.

Optimise engineering tools, workflows and automation (including CI/CD and AI-driven tools) to increase velocity, reliability and decision quality. Lead horizontal, cross-functional programmes (for example cloud migrations, GRC frameworks, GenAI adoption) that require alignment across Engineering, Product and customer-facing teams. Build, mentor and develop a globally distributed Engineering Operations and Program Management team, fostering a culture of accountability, continuous improvement and data-driven decision making.

These are the essentials you’ll need to get an interview 8–10+ years in Engineering Operations, software engineering leadership, Technical Program Management, transformation, strategy or business operations in a high-growth SaaS environment. Proven experience defining operational frameworks, delivery standards and KPI systems in a global organisation, with a focus on problem solving, programme scoping and execution. Strong understanding of SDLC, agile methodologies, CI/CD, DevOps and microservices architectures.

Advanced analytical skills using tools such as Excel, Looker, Tableau or similar, with the ability to turn data into clear, executive-ready narratives and recommendations. Demonstrated experience driving AI-related innovation, from evaluating opportunities and implementing tools to influencing adoption and change at scale. Track record of improving engineering processes, delivery predictability and cross-functional alignmen

Source listing: greenhouse_diligentcorporation