Senior Quality Assurance Automation Engineer

Job Title: Senior QA Engineer

Location: Onsite - Bangalore (Hybrid)

Budget - 30 LPA Max

**** Proficient in Automation Testing with Generative AI ****

Role Overview:

• We are looking for a Senior / Lead QA Engineer with hands-on experience in end-to-end testing of

  AI/ML-powered and cloud-based media platforms

  .
• The ideal candidate is not only technically proficient but also AI-aware in their QA approach

  informed on the latest AI test strategies, conversant with AI-powered tools for test case generation and execution

  , and comfortable experimenting with new AI-enabled frameworks that enhance automation efficiency.
• You will help

  set up intelligent QA systems integrated into CI/CD pipelines

  , driving test automation and turnaround time (TAT) efficiencies across the team.

Key Responsibilities:

• Own QA strategy, planning, and

  execution for AI/ML applications and microservices within the platform

  . 
• Design, automate, and optimize test cases across functional, integration, regression, and performance testing. 
• Validate AI/ML model outputs for accuracy, consistency, and bias; collaborate with data scientists to fine-tune test strategies for non-deterministic systems. 
• Stay informed on AI-driven testing approaches and tools; apply them to enhance test coverage and reduce manual effort. 
• Experiment with and

  onboard AI-enabled testing frameworks that support CI/CD linked automation and continuous validation

  . 
• Build and maintain intelligent test automation systems that improve overall system efficiency and TAT. 
• Test end-to-end content workflows involving video, audio, and text transcoding, speech-to-text, computer vision, content QC, and metadata enrichment. 
• Develop and maintain automated test frameworks using tools like Playwright, PyTest, Selenium, Postman, JMeter, or Robot Framework. 

• Integrate QA seamlessly into CI/CD pipelines (Jenkins, GitHub Actions, or similar).

• Collaborate closely with engineering, DevOps, and product teams to reproduce and resolve defects efficiently. 
• Contribute to improving QA standards, documentation, and test data management practices. 
• Support performance benchmarking, scalability, and regression testing of AI-enabled workflows. 

Required Skills & Experience:

• 6 to 10 years of QA experience in product development or enterprise platform environments.

• Strong understanding of SDLC, STLC, Agile methodologies, and defect lifecycle. 
• Proven experience in API testing, automation, and performance testing of distributed or cloud-based systems. 

• Familiarity with AI test strategies and exposure to AI/ML testing tools (for model validation, dataset evaluation, or automated test generation).

• Comfort with exploring and integrating new AI-driven frameworks to accelerate QA automation. 
• Familiarity with media domain concepts (audio/video codecs, subtitles, speech-to text, NLP, or computer vision) preferred. 

• Working knowledge of databases (SQL/NoSQL), scripting (Python preferred), and test automation frameworks.

• Experience with cloud platforms (AWS / Azure / GCP) and CI/CD pipelines.

• Strong analytical, documentation, and debugging skills. 
• Excellent communication and collaboration skills across cross-functional teams.