QA Analyst responsible for validating software quality at Toon Boom, leading end - to - end testing and troubleshooting for high - performance applications.
About the role
- Software Quality Engineer bridging traditional software quality and AI quality practices at Boomi. Designing testing strategies and ensuring product reliability in backend infrastructure and AI features.
Responsibilities
- Design and execute comprehensive test plans for backend services, APIs, and microservices architectures.
- Partner with Backend Engineers, AI Engineers, and Product teams to understand requirements and identify quality risks early in the development cycle.
- Develop automated testing frameworks using tools like Pytest, Playwright, unittest, and integration testing libraries.
- Build end-to-end test suites that validate the integration between backend systems, AI agents, databases & services.
- Advocate for quality-first practices, influencing architectural decisions and embedding testing into the development lifecycle.
- Design and implement automated evaluation frameworks for Generative AI features, including LLM / SLM model testing, prompt/ output validation, and behavioral assessment of agentic workflows.
- Develop quality metrics and evaluation methodologies for LLM-based applications, assessing accuracy, consistency, reliability, quality of AI/ML models.
- Create and maintain curated evaluation datasets and synthetic test data that cover edge cases, adversarial scenarios, and real-world variability.
- Leverage AI evaluation tools and frameworks & establish observability and monitoring requirements to quality assessment.
- Establish observability and monitoring requirements including structured logging, metrics collection, and tracing for both backend services and AI agent behavior.
- Implement quality gates and acceptance criteria and create test documentation including test plans, automation architecture, quality reports, and runbooks.
- Build strategies for testing in cloud environments & containerized execution.
- Implement performance testing, load testing, and reliability testing for production backend services and AI inference pipelines.
- Define and champion quality standards, best practices, and testing methodologies for both traditional backend systems and AI applications.
- Conduct code reviews with a focus on testability, quality patterns, and maintainability.
- Mentor junior quality engineers, sharing expertise in automation frameworks, AI testing approaches, and quality engineering principles.
- Communicate quality insights, risk assessments, and test results effectively to technical and non-technical stakeholders using tools like Jira and Confluence.
Requirements
- 2.5+ years of experience in software quality engineering, test automation, or software development with strong QA focus.
- Deep expertise in test automation frameworks and tools such as pytest, unittest, Selenium, Playwright etc.
- Strong programming skills in Python or Java with ability to write production-quality test code and automation frameworks.
- Proven track record building automated testing infrastructure for backend services and APIs.
- Experience with various testing methodologies: unit testing, integration testing, end-to-end testing, contract testing, performance testing, and test-driven development (TDD).
- Strong understanding of CI/CD pipelines and experience integrating automated tests into deployment workflows.
- Comfortable working in Linux/Unix environments for test execution and debugging.
- Familiarity with testing AI/ML applications or LLM-based systems, with understanding of unique quality challenges in non-deterministic systems.
- Knowledge of Generative AI concepts, agentic frameworks (ReAct, chain-of-thought, tool use), and LLM capabilities/limitations.
- Exposure to agentic AI patterns and knowledge of how to test tool orchestration, multi-turn conversations, and RAG systems.
- Excellent written and verbal communication skills with ability to document findings clearly and comprehensively.
- Strong collaboration skills working across cross-functional teams in Agile/Scrum environments.
- Experience with collaboration tools like Jira, Confluence, and Git for team workflows.
Benefits
- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
- Remote work options
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