As a Senior QA Engineer, you’ll be the person who checks and improves the quality of job architecture outputs we produce. You’ll work closely with our Data Science and Professional Services teams to review AI-generated data, spot issues, fix errors, and make sure each project is delivered accurately and on time.

This is a great role for someone who enjoys working with data,using AI agentic tools (e.g. Claude), has a sharp eye for detail. You’ll also help build and document the QA processes we use, so you’ll have a real say in how things are done.

What will you do as a Senior QA Engineer at Beamery?

Review and improve AI-generated outputs

• Check AI-generated role profiles against our quality standards, looking at skills, proficiency levels, and priority assignments to make sure they’re accurate and consistent.
• Spot errors, gaps, or inconsistencies in the data and fix them, making sure the overall structure stays intact.
• Work with the Professional Services team to manage the QA stage of each project, keeping things on track and within agreed timelines.
• Review Beamery’s Taxonomies and ensure the accuracy of Skills, Tasks and Role titles.
• Use AI agentic tools like Claude to review the output and implement deterministic agentic flow to accelerate and scale Beamery’s QA activities.
• Flag anything that needs a decision before sign-off and communicate clearly about what changes you’ve made and why.

Collaborate with Data Science

• Work with the Data Science team on defining, implementing and tracking QA metrics to enhance the AI output quality.
• Keep a clear record of the issues you find during QA, what went wrong, how often it happens, and what’s likely causing it, so the Data Science team can improve the AI pipeline.
• Help test pipeline updates between projects to check that fixes work as expected and don’t introduce new problems.
• Turn your QA findings into straightforward recommendations that the team can act on.

Help build our QA processes

• Write and maintain documentation for our QA workflows so that new team members can get up to speed quickly.
• Spot gaps in our current quality checks and suggest improvements, whether that’s adding new review steps, refining how we measure quality, or updating what “good” looks like.
• Help shape our quality standards as the product and customer needs evolve.

Who are we looking for?

• Experience (3+ years) in QA, data analysis, or a similar role where attention to detail and data accuracy mattered. Internships and placement years count.
• Experience (1+ years) in using Agentic tools for QA.
• Basic knowledge in Agentic technologies.
• A sharp eye for detail, you’re the kind of person who spots the inconsistency everyone else missed.
• An analytical mindset, when something looks wrong, you don’t just fix it; you want to understand why it happened so it doesn’t happen again.
• Good organisational skills, you can manage your own work across a few projects at once without things falling through the cracks.
• Clear communication, you can explain what you found and what you changed to both technical and non-technical people, in writing and in conversation.
• Comfort with ambiguity, some of our processes are still being built out, and you’re happy to help shape them rather than waiting for a playbook.

Nice to have

• Any exposure to AI-generated content, NLP outputs, or taxonomy/classification systems.
• An interest in HR technology, talent management, or how organisations think about skills and roles.
• Experience defining what “good” looks like for data, for example, writing acceptance criteria or quality metrics.
• You’ve helped set up a process or workflow from scratch, even informally.