QA Engineer

Mid-Level QA Engineer

iKnowHow Group is a leading Software & Robotics Solutions group of companies operating internationally for over 24 years, with 300+ professionals delivering innovative technology solutions across Energy, Telecommunications, Banking & Financial Services, and Public Sector industries. The group is structured into specialized subsidiaries, each focused on distinct technology domains and market verticals.

We are looking for a mid-level QA Engineer to work in new challenging outsourced projects.

You will design and execute test strategies, build automated testing pipelines on a cloud-native stack (primarily Azure, with GCP and AWS workloads), and partner with developers, product owners, and DevOps to embed quality into every stage of the software delivery lifecycle. You will also help the team adopt AI-assisted testing approaches that increase coverage, reduce flakiness, and accelerate release cadence.

Responsibilities:

• Design, develop, and maintain comprehensive test plans and test cases for web, API, and mobile components of the client's digital insurance platforms.
• Execute functional, regression, integration, and end-to-end test suites across multiple environments.
• Perform thorough REST API testing, validating request/response contracts, error handling, and edge cases relevant to policy, claims, and customer journeys.
• Conduct UI testing.
• Define and implement performance testing strategies, identifying bottlenecks before they reach production.
• Build and maintain automated test suites integrated into CI/CD pipelines.
• Collaborate with DevOps and development teams to ensure automated quality gates are embedded at every stage of the software delivery lifecycle.
• Continuously improve test coverage, reliability, and execution speed of automation frameworks.
• Apply AI-assisted testing tools, to accelerate test case generation, exploratory testing, and test data synthesis from requirements, user stories, and API specifications.
• Use AI assistance to translate business rules and acceptance criteria into automated test scripts, reviewing and hardening generated tests before they enter the regression baseline.
• Evaluate and pilot AI-driven testing platforms and recommend the right balance between traditional automation and AI-assisted approaches.
• Define guidelines and guardrails for responsible use of AI in QA workflows.
• Manage test cases, test runs, and defect tracking, maintaining clear and up-to-date test documentation.
• Participate in sprint ceremonies, providing QA estimates, risk assessments, and sign-off criteria for new features and bug fixes.
• Collaborate with developers during code reviews and design sessions to identify testability concerns and promote quality-by-design.
• Champion best practices in software quality across the team, contributing to internal QA guidelines and standards.