AI Governance and Testing Manager in Manchester

PwC UK Manchester, England, United Kingdom

Our AI & Modelling (AI&M) team is a diverse group of 500+ individuals across the UK and India, with deep experience across the banking, insurance, commercial and government sectors. We are expanding rapidly as clients look to safely adopt AI whilst realizing its benefits.

About The Role

This role sits at the forefront of how organisations build, deploy and oversee advanced AI systems. As an AI Governance and Testing Manager, you will join a team that helps organisations adopt AI responsibly and with confidence. You will work closely with clients to shape practical approaches for evaluating and governing AI models, including generative AI systems and emerging agentic frameworks. You will contribute to the development of governance frameworks and processes that ensure AI solutions meet ethical, regulatory and operational expectations – including work in model risk, data privacy, data governance, technology and cyber security.

This work spans a wide range of AI programmes across industries, providing opportunities to influence decision‑making, guide major AI adoption initiatives and help shape emerging industry best practice. Alongside this, you will play a key role in developing AI evaluation and monitoring methodologies, strengthening how organisations understand and manage the risks and opportunities created by AI.

A central aspect of the role is leading automated testing programmes that assess how AI systems perform in practice and at scale. This includes designing and leading automated testing approaches such as scenario‑based testing, red‑team and ongoing monitoring of non‑deterministic AI systems in production. You will oversee end‑to‑end delivery of AI governance and testing workstreams, acting as a key client contact and ensuring high‑quality, defensible outcomes. You will coach and develop junior colleagues, review and challenge their work, and help build our firm‑wide capability in AI governance and testing.

What Your Days Will Look Like

• Design and implement AI governance frameworks, policies, processes and operating models that enable safe, responsible and compliant AI adoption across the development lifecycle.
• Lead AI use case risk assessments, identifying vulnerabilities and control gaps, and designing proportionate mitigations such as guardrails, governance checkpoints and automated controls to support safe and scalable deployment.
• Lead the design and delivery of AI evaluation programmes, including automated and scenario‑based testing to assess performance, robustness, safety, reliability and failure modes.
• Develop and refine AI evaluation methodologies and reusable testing assets, contributing to research that advances the team’s approach to generative and agentic AI assessment.
• Interpret evaluation outputs and provide clear, evidence‑based recommendations on model risks, limitations, controls, and deployment readiness.
• Manage day‑to‑day engagement with client teams and internal stakeholders across PwC, guiding junior colleagues and ensuring high‑quality delivery across governance, testing and advisory projects.
• Contribute to new propositions, tools and thought leadership that enhance the team’s capabilities in AI evaluation, governance and risk management.
• Maintain an up‑to‑date view of regulatory, technological and industry developments, sharing insights with the team and helping to shape leading‑edge best practice in AI governance and testing.

Qualifications

• Experience designing AI governance frameworks aligned to recognised standards or regulations (e.g. EU AI Act, NIST AI RMF, ISO 42001, SS1/23, Responsible AI principles).
• Experience implementing governance processes across the AI lifecycle, such as use‑case risk assessments, AI model documentation requirements, monitoring standards, or the design of proportionate controls.
• Experience designing and implementing data privacy and data governance approaches for AI systems, including GDPR‑compliant data usage, retention, lineage and access controls across the AI lifecycle.
• Experience designing and executing structured testing of Gen AI or ML systems, such as scenario‑based evaluations or batch testing.
• Ability to interpret model behaviour and testing outputs, translating technical findings into clear governance, risk and compliance implications for senior stakeholders.
• Strong Python skills, including experience developing ML, GenAI and/or agentic model pipelines.
• Strong written and verbal communication skills, with experience producing structured evaluation reports, governance documents, technical assurance outputs and client‑ready presentations.
• Experience leading workstreams or managing junior colleagues, coordinating delivery across multiple projects, and contributing to the development of new methodologies, tools, and client propositions.

Benefits

No matter where you may be in your career or personal life, our benefits are designed to add value and support, recognising and rewarding you fairly for your contributions. We offer a range of benefits including empowered flexibility and a working week split between office, home and client site; private medical cover and 24/7 access to a qualified virtual GP; six volunteering days a year and much more.

Seniority level: Mid‑Senior level

Employment type: Full‑time

Job function: Quality Assurance

Industries: Accounting