AI QA Engineer

At Conscensia, you’ll have the unique opportunity to work as part of our team while contributing to innovative projects for our trusted customers. This position is for a project with Unik System Design, where you’ll collaborate closely with the customer’s team while enjoying all the benefits and support of being a Conscensia colleague.

Project overview

Unik System Design (USD) is a Danish company with offices in Vejle (HQ), Aalborg and Copenhagen. Unik System Design delivers software products for the housing/property management industry. The products are market-leading in Denmark.
List of technologies: GitHub Copilot, Azure DevOps, C#, .NET, MSSQL, RabbitMQ, Entity Framework Core, Angular

Responsibilities

You will work closely with developers, architects, and product owners to ensure that AI‑generated test artifacts, results, and recommendations are correct, relevant, and aligned with real product risk. You will spend minimal time executing tests. Instead, most of your effort will focus on governing the quality of AI-first development through:

• Defining feature test strategies and quality expectations ahead of agent‑driven development
• Defining the right inputs, context, constraints, and prompts for AI‑driven test generation
• Reviewing, validating, and challenging AI‑generated test cases, scenarios, and conclusions
• Deciding what AI output can be trusted, what requires refinement, and what must be rejected
• Establishing and evolving practical QA guardrails for when and how AI is used
• Targeted test execution will be used selectively to validate critical paths and challenge AI assumptions.
• Working with development teams to integrate validated AI output into automated pipelines

You will be embedded in a development area while collaborating closely with the QA Lead and other QA colleagues across teams to evolve shared QA standards and practices that support responsible and consistent AI‑first development

Requirements

• 3+ years of experience in QA and test automation
• ISTQB certification
• Strong ability to assess correctness, relevance, and risk in test artifacts
• Hands-on experience with AI-driven development and test generation, including strong understanding of AI limitations, risks, and validation requirements

Will be an advantage:

• Experience with Cypress, TypeScript, or similar automation stacks
• Experience testing cloud‑based or distributed systems
• Interest in shaping QA guardrails and boundaries for AI usage