We are always looking for new ideas and diverse perspectives to question established thinking and drive meaningful change. Great pricing is built on trust, innovation and precision, so our aim is to ensure customers receive a fair and accurate price based on their individual risk, supporting fair outcomes, while delivering sustainable and profitable growth for our company.

Pricing is more than just a number – it’s a strategic capability. At the heart of Hastings is deep risk insight – continually improving how we assess, segment and price risk through data and analytics.

The Role:

We are seeking a senior, hands-on QA leader to drive technological transformation of testing across our pricing platforms. This role is responsible for improving quality, pace, and confidence of delivery through modern testing techniques, automation, and AI-enabled approaches, while leading and developing a high-performing QA function. The role operates across our in-house based rating engine and Azure/GitHub-based engineering landscape. Working closely with pricing engineers, ML engineers, and underwriting teams, you will modernise how testing is designed, executed, and governed, reducing duplication of effort and materially lowering post-live issues.

This role combines hands-on technical involvement, strong people leadership, and strategic ownership of testing capability, tooling, and environments.

Key Responsibilities

• Lead end-to-end QA strategy and execution across all underwriting lines of business, ensuring testing supports high-quality delivery at pace.
• Design, implement, and continuously evolve the QA strategy covering pre-live testing, post-release monitoring, and live issue investigation, with a focus on improving quality, pace, and confidence of delivery.
• Provide hands-on technical leadership in reviewing test strategies, automation design, and investigation of complex or high-impact defects, including interrogation of rating behaviour and data inputs.
• Lead the strategic and practical use of test automation, ensuring automation is targeted, maintainable, and focused on the highest-risk areas.
• Drive improvements in automation and tooling to reduce manual effort and strengthen preventative quality controls, applying AI-assisted techniques where they provide clear, measurable benefit.
• Work closely with pricing engineers and ML teams to apply AI-assisted testing techniques where they add value, ensuring solutions are governed and suitable for a regulated environment.
• Own post-release quality activities, including monitoring, alerting, and validation of controls, ensuring issues are detected early and feedback loops are effective.
• Improve the efficiency, stability, and reliability of QA test environments to enable comprehensive data testing with minimal environment-related failures.
• Support incident RCA activity by providing testing insight, evidence, and analysis, and ensure learnings are embedded into improved testing practices.
• Line-manage QA Leads and the Automation Manager, providing clear direction, prioritisation, coaching, and performance support.
• Ensure QA activities are focused on preventing customer harm and supporting compliance with regulatory and internal governance requirements.
• Maintain strong communication and organisational discipline to manage multiple initiatives and report progress, risks, and outcomes clearly and consistently.
• Develop and maintain QA documentation, standards, and artefacts to ensure testing practices are consistent, auditable, and aligned with internal and regulatory requirements.
• Define and track quality metrics such as defect trends, test effectiveness, automation coverage, and release readiness to support data-driven decisions.
• Support recruitment and development of QA talent through active hiring involvement, regular one-to-one engagement, mentoring, and creating an environment where team members can perform and grow.

Skills, Knowledge and Expertise

• Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.
• Strong experience leading QA or test engineering teams in complex, data-driven or regulated technology environments.
• Hands-on technical capability, with the ability to write, read, and review code and actively contribute to test design and automation decisions.
• Strong proficiency in Python, including writing and reviewing automated tests and debugging failures in complex rules-based or decisioning systems.
• Proven experience designing and maintaining test automation, including API and integration testing using frameworks such as pytest, with working knowledge of UI tools such as Selenium, Playwright, or Cypress where appropriate.
• Experience applying AI-assisted testing tools to improve coverage, efficiency, or defect detection, with clear understanding of governance and control requirements.
• Practical experience working with Git/GitHub, CI/CD pipelines, and Azure-based engineering environments.
• Strong understanding of modern testing practices, including risk-based testing, shift-left quality, and end-to-end assurance.
• Experience working with test environments and test data, including validation of complex inputs and outputs using SQL and data comparison techniques.
• Familiarity with test management and defect tracking tools such as Azure DevOps and producing clear, meaningful quality metrics.
• Excellent leadership skills, with experience managing senior QA roles and automation specialists.
• Strong stakeholder-management and influencing skills, with the ability to balance technical, commercial, and governance considerations.
• Excellent problem-solving skills, with the ability to navigate complex pricing and engineering challenges and deliver robust solutions.
• Strong communication skills, able to clearly explain technical quality risks and solutions to both technical and non-technical stakeholders.
• Experience working in Agile delivery environments and collaborating closely with engineering, data, and ML teams.

Interview Process:

Recruiter screening call