Job description
QA Manager | Manchester (Hybrid)
Join a business right at the beginning of their AI journey!!
"We are building a new AI capability from the ground up as part of a wider transformation of the business and this is an opportunity to join right at the beginning of our journey: shaping the strategy, foundations, delivery approach and culture rather than inheriting somebody else's playbook."
The role:
Joining as the QA | Test Manager, you will will establish the quality strategy, automation framework and release confidence for a new portfolio of AI-enabled products. You will combine strong software testing discipline with new approaches for evaluating model behaviour, generated outputs, data quality, safety and live performance.
Traditional pass-or-fail testing is not enough for AI systems. You will define how the organisation tests both deterministic software and probabilistic AI behaviour, creating repeatable evaluation, automation and assurance from the outset. This is a hands-on leadership role: you will set the strategy, build the foundations and help delivery teams embed quality throughout the lifecycle.
Day-to-day, your role involve the following:
- Define the end-to-end quality engineering and test strategy for AI-enabled products, services and automations.
- Build scalable automation across APIs, integrations, user journeys, data pipelines, regression, performance and security testing.
- Create evaluation frameworks for AI outputs, covering accuracy, relevance, groundedness, consistency, safety, bias and task completion.
- Establish representative test datasets, golden test sets, scoring approaches, thresholds and release criteria.
- Design testing for failure modes such as hallucination, prompt injection, data leakage, harmful output, degraded models and unreliable external services.
- Embed automated quality gates within CI/CD and define appropriate human review for higher-risk use cases.
- Partner with product and design to turn user expectations into measurable acceptance and quality criteria.
- Work with architecture, engineering, data and security to improve testability, observability and root-cause diagnosis.
- Define production monitoring, feedback loops and incident learning to detect quality drift after release.
The ideal QA Manager we are looking for:
An experienced QA / Test Manager, you will have experience building teams and processes from the ground up, have a strong interest in AI first engineering and AI Products and ideally offer experience in the following:
- A strong background in quality engineering, test automation and modern software delivery environments.
- Experience creating automation frameworks and quality strategies across APIs, web applications, integrations, data and cloud services.
- Experience testing LLM applications, RAG, machine-learning systems, conversational products or intelligent automation.
- Strong knowledge of CI/CD, non-functional testing, observability, test data and risk-based assurance.
- An understanding of how testing probabilistic AI behaviour differs from conventional deterministic systems.
- The ability to define measurable quality thresholds where there may not be one universally correct answer.
- Hands-on technical credibility alongside the leadership skills to establish standards and influence delivery teams.
- A practical, proportionate approach that improves delivery speed and confidence rather than turning quality into a final-stage gate.
Why join and next steps:
You will have genuine influence, visibility and the space to build well from day one. The team will tackle meaningful business problems, combining rapid experimentation with the standards required to make AI secure, trusted and valuable at scale. If you enjoy creating clarity where there is ambiguity and want your work to shape an organisation's future, this is a rare opportunity to do exactly that.
Apply today, we are looking to move quickly - the quicker we build the team, the quicker we can start moving ahead with the AI plan.
Day-to-day
Develop and maintain software applications to meet client requirements.
Collaborate with cross-functional teams to design scalable solutions.
Troubleshoot and resolve technical issues promptly.
Participate in code reviews to ensure code quality and standards.
Document software functionality and update technical manuals.
Monitor system performance and implement improvements.
Stay updated with emerging technologies and integrate them as needed.
Provide technical support and training to end-users.
Apply today
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