Engineer - ML QA (Inception42)

Inception42, a G42 company, is the region\u2019s leading innovator of AI-powered domain-specific as well as industry-agnostic products, built on a rich heritage of research and development. Within the G42 ecosystem, Inception functions as the core intelligence layer \u2013 transforming data and compute infrastructure into real-world, applied AI solutions. Beyond its commercial endeavors, Inception is committed to creating positive societal impact. For more information, please visit www.inception42.ai We are looking for a QA Engineer to validate AI-enabled financial applications and enterprise platforms across user experiences, APIs, data flows, and integrated business workflows. You will design and execute manual and automated tests, turn product requirements into measurable acceptance criteria, and provide clear evidence of product quality throughout the software delivery lifecycle. You will work closely with Engineering, Product, Architecture, AI, Security, and Compliance teams in a delivery environment where application behavior can span conventional software and probabilistic AI components. The role requires disciplined testing, strong technical judgment, and ownership of defects from discovery through verification. \u2022 Design and execute risk-based test plans for functional, integration, regression, usability, accessibility, and performance testing. \u2022 Translate product requirements and business workflows into clear acceptance criteria, test scenarios, and traceable test evidence. \u2022 Validate AI application behavior against approved scenarios, including response relevance, consistency with authorized source content, instruction adherence, and appropriate handling of unsupported requests. \u2022 Test conversational experiences across multi-turn interactions, context retention, session isolation, ambiguous inputs, and recovery from errors. \u2022 Validate document ingestion and retrieval workflows, including source relevance, reference accuracy, data freshness, and user access permissions. \u2022 Test AI-driven orchestration and tool integrations for correct action execution, confirmation steps, authorization boundaries, retries, and prevention of duplicate or unintended actions. \u2022 Verify safeguards against prompt injection, sensitive information disclosure, and unauthorized access across users and tenants. \u2022 Assess behavior during AI service outages, timeouts, incomplete responses, and dependency failures, including fallback paths and user-facing messages. \u2022 Build and maintain reliable automation for UI, API, integration, and data validation testing using the team\u2019s established frameworks. \u2022 Maintain reusable business scenarios, representative test data, and regression suites that cover changes to prompts, configurations, integrations, and application releases. \u2022 Integrate automated smoke and regression tests into CI/CD pipelines to provide timely, actionable feedback. \u2022 Validate financial calculations, reconciliations, reporting, access controls, and audit trails across AI-assisted and conventional workflows. \u2022 Evaluate end-to-end responsiveness, concurrent usage, and application stability under expected and peak workloads. \u2022 Own defect documentation, triage, retesting, and root-cause collaboration, and convert production findings into stronger test coverage. \u2022 Maintain requirements traceability, test results, defects, and quality reporting in Azure DevOps, and communicate release risks with clear supporting evidence. Strong software quality fundamentals, including test design, exploratory testing, defect analysis, and risk-based coverage. \u2022 Experience testing production web or cloud applications across UI, API, integration, and end-to-end workflows. \u2022 Hands-on experience building or maintaining automated tests with tools such as Playwright, Selenium, Cypress, REST Assured, Postman, or comparable frameworks. \u2022 Working proficiency in at least one programming language used for test automation, such as Python, TypeScript, or Java. \u2022 Ability to validate REST APIs, authentication and authorization controls, service integrations, and failure behavior. \u2022 Strong SQL skills and experience verifying data flows, transformations, calculations, and reporting outputs. \u2022 Familiarity with Git, CI/CD pipelines, Agile delivery, and cloud-based application environments. \u2022 Understanding of AI application concepts such as prompts, conversational context, retrieval-augmented generation, and tool execution, or the ability to learn them quickly. \u2022 Ability to design repeatable checks for variable system responses using clear business rules and expected outcomes. \u2022 Strong debugging and communication skills, with the judgment to distinguish blocking defects from acceptable residual risk. \u2022 An ownership mindset and the ability to execute across ambiguity while collaborating closely with engine