Quality Assurance Developer

MindBridge is the global leader in AI-powered financial risk intelligence. Our platform, MindBridge AI™ is enabling finance and audit professionals to build the AI-powered finance department of the future. With over 120 billion financial transactions analyzed with MindBridge’s AI, we set the standard for innovation, scalability, and customer satisfaction.

At MindBridge, we’re driven by innovation and excellence, united as a team to revolutionize financial integrity. Here, your ideas matter, and your efforts make a meaningful impact. If you’re passionate about using AI to drive positive change, MindBridge is the perfect fit. What distinguishes us is our unwavering commitment to our values: Innovation, Collaboration, and Integrity. These principles foster a vibrant workplace culture, where appreciation and a strong sense of community flourish.

Role Overview

We are looking for a QA & Test Automation Developer to help us evolve how software quality is built, automated, and scaled across MindBridge.

Strong testing fundamentals are essential to this role. We are looking for someone who understands common testing heuristics, can identify meaningful product risks, and knows how to test and verify software beyond the obvious happy paths. You will use agentic tools to apply those skills faster and at greater scale without compromising testing depth or judgment.

You will design and maintain automated test suite, improve our quality engineering frameworks and delivery pipelines, and expand the use of AI agents within our QA processes. This includes creating, configuring and using agentic tools to accelerate test creation, analysis, failure triage, coverage assessment, and other recurring quality workflows.

As our product and software development practices become increasingly AI-native, you will also contribute to how we validate AI-powered features. Having direct experience testing AI agents, LLM-based features, or other non-deterministic systems is a strong asset.

What You Will Do

Quality engineering & automated testing

• Apply strong testing fundamentals and heuristics to identify product risks, edge cases, failure modes, and gaps in expected behaviour
• Investigate failures and unexpected behaviour and act of them.
• Configure and use agentic tools with various degree of autonomy, to accelerate test creation, maintenance, analysis, failure triage, and other recurring QA activities.
• Advocate for testability and quality throughout the development lifecycle.
• Improve the reliability, performance, and scalability of our test frameworks, internal tooling, and automated quality gates.
• Evaluate AI-generated outputs critically and ensure appropriate validation and human oversight remain part of the testing process.

Testing AI-powered systems

• Contribute to test strategies for AI-powered, LLM-based, and agentic product capabilities.
• Help define how non-deterministic behaviour should be evaluated, including expected behaviour, quality thresholds, regression approaches, and failure analysis.
• Validate areas such as model responses, tool usage, grounding, consistency, error handling, latency, and end-to-end agent behaviour where applicable.

Collaboration & continuous improvement

• Collaborate with Engineering, Product, and other technical teams to make quality an integral part of software development.
• Share testing patterns, tools, and lessons learned, and continuously look for ways to improve testing effectiveness and delivery speed.

Required Qualifications

• Strong software testing fundamentals, such as critical thinking, exploratory testing, test design, risk-based testing, common testing heuristics, and the ability to reason about customer and product impact.
• Hands-on experience designing and developing automated tests for modern software applications.
• Strong programming skills in at least one language commonly used for test automation or engineering, such as TypeScript/JavaScript or Python.
• Experience with modern test automation frameworks
• Experience working with CI/CD pipelines and incorporating automated testing into software delivery workflows.
• Ability to troubleshoot complex software and automated test failures across application, test, data, and infrastructure layers.
• Practical experience leveraging AI-assisted development capabilities to automate or improve engineering and QA workflows.
• Strong collaboration and communication skills, with the ability to work effec…