Job Description

• Owning and evolving the QCS technology strategy, translating product strategy into a clear roadmap covering architecture, engineering, data, AI, security, infrastructure and platform capability, to deliver measurable customer and business outcomes.
• Embedding AI as fundamental to the QCS technology strategy, operating model and engineering culture, to materially improve customer experience, product capability, engineering productivity and operational efficiency.
• Owning the QCS Azure and architecture strategy, leading the evolution towards a modern, API-first and integration-friendly platform, to provide a secure, scalable and cost-effective foundation for growth.
• Ensuring predictable delivery through reliable CI/CD pipelines, automation and AI-assisted development, in order to maintain consistently high standards of engineering execution across QCS.
• Acting as the technical authority for QCS, diagnosing and resolving intricate technical challenges and mitigating technical risk, to maintain system reliability and security at scale.
• Leading and developing the QCS engineering organisation, mentoring engineering leaders and building capability, in order to attract and retain exceptional technical talent and leave the organisation technically stronger.

• Significant experience as a senior engineering leader in a SaaS, software or technology-led business, with a track record of developing and executing technology strategy to support significant growth.
• Strong technical depth in modern cloud-native architecture, distributed systems, APIs, integrations, data platforms and scalable SaaS architecture, with substantial hands-on Azure experience (or another major cloud platform).
• Proven success building and leading high-performing, multidisciplinary engineering teams, translating complex business strategies into actionable technical plans with cross-departmental impact.In-depth knowledge of automated testing, CI/CD, infrastructure as code, observability, reliability engineering, security and technical debt management in large-scale environments.
• Experience working in a regulated, security-conscious or data-sensitive environment, with a strong understanding of secure-by-design principles and data protection.
• A conviction that AI will fundamentally change how software companies build products and operate, with demonstrable experience using AI, machine learning or generative AI to create customer or business value, including a working understanding of modern AI architectures such as LLMs, retrieval, agents, evaluation and AI governance.
• Ability to commute to London on a hybrid basis (once per week). 

By enabling flexibility in how we work and prioritising employee wellness, we empower our team to do and be their best. Key benefits include private health and group accident insurance, an Employee Assistance Program (EAP) for confidential support, and Loyalty Awards for long-service employees.