QA & Process Improvement Engineer

A unique opportunity for someone with experience in insurance claims, quality assurance, audit, operational excellence, or business analysis to help shape how MPL uses quality insight, process improvement, automation, and AI to build the next generation of claims handling.

Are you passionate about improving processes, solving operational problems, and exploring how AI can transform the insurance industry?

Why Join MPL?

Join a growing and innovative organisation where you'll have the opportunity to shape a newly created role, work on AI, automation, and digital transformation initiatives, collaborate across claims, technology, and operational teams, influence business-wide improvements, and develop your career as the role evolves.

You will work closely with business stakeholders, IT teams, and third-party vendors to ensure solutions are well defined, effectively implemented, and aligned with strategic objectives.

About This Role

You'll play a key role in identifying opportunities where automation and AI can improve efficiency, reduce manual effort, and enhance customer outcomes. Working alongside operational and technology teams, you'll help turn innovative ideas into practical solutions that make a real difference.

Role Requirements

• Undertake targeted audits across our operational teams (Motor, Property & Liability).
• Review claims processes and identify unnecessary manual activity, duplication, and rework.
• Identify trends, risks, strengths, and opportunities for improvement.
• Design and implement improvement strategies to support operational best practice.
• Work with our Technology team to identify opportunities for AI and automation.
• Translate operational challenges into technology solutions.
• Support the testing and implementation of new tools and processes.
• Measure whether changes have delivered the expected improvements.
• Build business cases and calculate the ROI of improvement opportunities.
• Support the development of standalone QA and audit services for clients.

You don't necessarily need to be an AI specialist. What's more important is that you're interested in how technology can solve real operational problems and that you can work with technical colleagues to turn ideas into practical solutions.

Your Key Skills

• Strong analytical and problem-solving skills.
• Insurance or claims knowledge is desirable.
• Experience reviewing operational processes.
• Understanding of QA methodologies and root cause analysis.
• Confidence working with operational data.
• Strong attention to detail.
• Ability to communicate and influence across different teams.
• A naturally curious and improvement-focused mindset.
• Confidence challenging existing ways of working.
• Ability to take an improvement initiative from idea through to implementation.

Experience within insurance or claims would be beneficial, as would exposure to AI, automation, Lean, Six Sigma, process mapping, or technology change. However, we are equally interested in candidates from other operational environments who can bring new ideas and ways of thinking.

QA & Process Improvement Engineer

MPL Technology

A unique opportunity for someone with experience in insurance claims, quality assurance, audit, operational excellence, or business analysis to help shape how MPL uses quality insight, process improvement, automation, and AI to build the next generation of claims handling.

Are you passionate about improving processes, solving operational problems, and exploring how AI can transform the insurance industry?

Why Join MPL?

Join a growing and innovative organisation where you'll have the opportunity to shape a newly created role, work on AI, automation, and digital transformation initiatives, collaborate across claims, technology, and operational teams, influence business-wide improvements, and develop your career as the role evolves.

You will work closely with business stakeholders, IT teams, and third-party vendors to ensure solutions are well defined, effectively implemented, and aligned with strategic objectives.

About This Role

You'll play a key role in identifying opportunities where automation and AI can improve efficiency, reduce manual effort, and enhance customer outcomes. Working alongside operational and technology teams, you'll help turn innovative ideas into practical solutions that make a real difference.

Role Requirements

• Undertake targeted audits across our operational teams (Motor, Property & Liability).
• Review claims processes and identify unnecessary manual activity, duplication, and rework.
• Identify trends, risks, strengths, and opportunities for improvement.
• Design and implement improvement strategies to support operational best practice.
• Work with our Technology team to identify opportunities for AI and automation.
• Translate operational challenges into technology solutions.
• Support the testing and implementation of new tools and processes.
• Measure whether changes have delivered the expected improvements.
• Build business cases and calculate the ROI of improvement opportunities.
• Support the development of standalone QA and audit services for clients.

You don't necessarily need to be an AI specialist. What's more important is that you're interested in how technology can solve real operational problems and that you can work with technical colleagues to turn ideas into practical solutions.

Your Key Skills

• Strong analytical and problem-solving skills.
• Insurance or claims knowledge is desirable.
• Experience reviewing operational processes.
• Understanding of QA methodologies and root cause analysis.
• Confidence working with operational data.
• Strong attention to detail.
• Ability to communicate and influence across different teams.
• A naturally curious and improvement-focused mindset.
• Confidence challenging existing ways of working.
• Ability to take an improvement initiative from idea through to implementation.

Experience within insurance or claims would be beneficial, as would exposure to AI, automation, Lean, Six Sigma, process mapping, or technology change. However, we are equally interested in candidates from other operational environments who can bring new ideas and ways of thinking.