QA Automation Engineer
Description
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 & Experience
Quality 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 architecture
AI/ML Testing (Bonus): Exposure to LLM validation, visual regression testing, and asynchronous orchestration workflows for AI-generated content.