QA Automation Engineer
1 day ago
Key Responsibilities:Led end -to -end QA strategy for AI -driven platforms (Velocity & Agentic AI), ensuring quality across UI, API, backend, cloud integrations (e.g., LLMs), and multimedia outputs (video, image, audio, JSON).Designed and executed functional and exploratory testing plans to validate end -to -end multimedia workflows, including video rendering accuracy, API reliability, and agent fallback logic.Built robust automation frameworks from scratch for UI, API, backend, and system -level testing, optimised for speed, maintainability, and test coverage.Owned and integrated automated test pipelines into CI/CD workflows, accelerating feedback loops and reducing release cycle times.Conducted performance, load, and resilience testing to identify quality risks like concurrency issues, processing failures, and LLM timeouts; ensured platform stability under scale.Collaborated closely with engineering, product, design, and AI teams to uphold quality in fast -paced agile development cycles; contributed QA insights to sprint planning and retrospectives.Skills & ExperienceQuality Assurance Leadership: Over 7 years of experience owning QA strategy and execution in product/platform environments, ensuring quality across scalable web applications, APIs, and backend services.Multimedia & Platform Testing: Hands -on testing of complex multimedia workflows (video, audio, image), with exposure to cloud -native, ML -based, and agent -driven architectures.Automation Engineering: Built automation frameworks from scratch covering unit, integration, UI, and API levels; integrated tests into CI/CD pipelines to streamline releases.Risk & Coverage Management: Proactively identified gaps in test coverage and implemented strategies to mitigate potential quality and performance risks.Cloud & System Knowledge (Bonus): Familiar with cloud infrastructure (AWS), distributed messaging systems (Kafka/SQS), and microservices architectureAI/ML Testing (Bonus): Exposure to LLM validation, visual regression testing, and asynchronous orchestration workflows for AI -generated content.
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