Quality Assurance Engineer

Our client is an AI-powered technology company building and deploying intelligent systems that help enterprises and public sector institutions modernize operations improve decision-making and scale efficiently. Operating at the intersection of applied research advanced analytics and software engineering they deliver AI-driven platforms across finance healthcare and government with a sharp focus on translating emerging technology into production-ready solutions that deliver measurable impact.

They are currently building a fraud detection product and expanding their AI platform portfolio. This is an early-stage start up environment where the people they hire will shape not just what they build but how they build it.

About the Role

We are looking for a Quality Assurance Engineer to own the quality function. This is a founding QA role - you will be setting the standards building the frameworks and ensuring that the AI-driven products we ship are reliable secure and production-ready.

We need someone who thinks deeply about quality builds automation from the ground up and is comfortable working closely with engineers and product teams in a fast-moving high-stakes environment.

QA Strategy & Ownership

• Define and own the QA strategy across the companys product suite starting with the fraud detection platform.
• Establish quality standards testing frameworks and processes that scale as the product portfolio grows
• Advocate for quality at every stage of the development lifecycle from requirements through to production deployment

Test Automation

• Design build and maintain robust automated test suites (functional regression integration end-to-end)
• Build automation infrastructure from scratch selecting the right tools and frameworks for the tech stack
• Ensure continuous testing is embedded in CI/CD pipelines

AI & API Quality

• Develop testing strategies for AI/ML model outputs including accuracy validation edge case handling bias detection and performance benchmarking
• Design and execute API testing frameworks to validate data flows integrations and system reliability
• Define data quality standards for the inputs and outputs that feed the companys AI systems

Fraud Detection Product QA

• Lead end-to-end testing of the fraud detection product across functional performance security and edge-case scenarios
• Design test cases that reflect real-world transaction patterns adversarial inputs and failure modes
• Work closely with the engineering and data science teams to validate model performance against defined thresholds

Collaboration & Process

• Partner with engineers data scientists and product managers to embed quality into the development process
• Document and maintain test plans test cases and quality reports
  
  
  

• Bachelors degree in Computer Science Software Engineering or a related field
• 5 years of experience in software quality assurance with significant automation experience

• Proven track record of building QA frameworks and automation infrastructure from scratch
  
• Strong experience in API testing (REST/GraphQL) using tools such as Postman REST-assured or similar
  
• Proficiency in at least one automation framework (Selenium Playwright Cypress PyTest or similar)
  
• Experience with CI/CD pipelines (GitHub Actions Jenkins GitLab CI or similar)
  
• Solid understanding of software development processes and the ability to work effectively with engineering teams
  
• Experience testing data-intensive or AI/ML systems is a strong advantage
  
• Experience in fintech payments or fraud detection systems is a strong advantage.
  
  What Were Looking For
  
  • Someone who takes genuine ownership not waiting to be told what to test but proactively identifying risk
    
  • Comfortable working in ambiguity and building structure where none exists
    
  • A systems thinker who can see how individual components interact and where things are likely to break
    
  • Strong communication skills able to articulate quality risks clearly to both technical and non-technical stakeholders
    
  • An eye for edge cases adversarial inputs and failure modes that others miss.