QA Automation Engineer

Job 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.

Requirements

ob Description and Experience : 7+ years total experience, 5+ years in automation. Responsibilities : SDET-II

• Designed reusable CSS templates for website pages, implementing background, positioning, text, borders, margins, padding, and table styling.
• Applied optimization techniques such as sprites to reduce page size and load times, improving overall user experience.
• Developed responsive UI with React JS, using components, forms, events, keys, router, animations, and Flux concepts.
• Implemented single-page navigation with React-Router, drag-and-drop features with React-Draggable, and autocomplete search using React-Autocomplete integrated with Google Maps. Consumed SOAP and RESTful web services for handling large XML / JSON data; used Node.js as a proxy for RESTful services with a PostgreSQL database.
• Applied OOP principles to create reusable UI components; maintained version control with Git / GitHub, and collaborated across testing, product management, and business teams for issue resolution.
• Experienced with AWS integration, Docker containers, and creating Docker images to deploy applications efficiently.
• Gen AI must have
• Lead the development and implementation of AI-driven automation solutions using Python, TensorFlow, and AWS, resulting in a 30% increase in operational efficiency.
• Collaborated with cross-functional teams to identify automation opportunities and design ML models to address business challenges.
• Conducted data analysis and feature engineering using Pandas and NumPy to extract valuable insights and improve model performance.