Qa Engineer-Clear AI @ Prime Focus

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Qa Engineer-Clear AI

Prime Focus
6 - 10 years
Bengaluru
10 days ago
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Job Description

Role & responsibilities

Title:

Senior QA Engineer CLEAR AI

Job 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.

Employer Name:

Prime Focus Technologies

Location:

Bangalore / Hybrid

Experience Required:

6 - 10 years

Must Haves:

- 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

- 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

Overall Skills Needed:

- End-to-end testing of AI/ML-powered and cloud-based media platforms

- Designing, automating, and optimizing test cases across functional, integration, regression, and performance testing

- Validating AI/ML model outputs for accuracy, consistency, and bias

- Staying informed on AI-driven testing approaches and tools

- Experimenting with and onboarding AI-enabled testing frameworks

- Building and maintaining intelligent test automation systems

- Testing end-to-end content workflows involving video, audio, and text

- Developing and maintaining automated test frameworks

- Integrating QA into CI/CD pipelines

- Collaborating with engineering, DevOps, and product teams

- Contributing to improving QA standards, documentation, and test data management practices

- Supporting performance benchmarking, scalability, and regression testing of AI-enabled workflows

Key Responsibilities:

- Own QA strategy, planning, and execution for AI/ML applications and microservices within the CLEAR AI 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

Experience with Volume Scale of Operations:

Own QA strategy, planning, and execution for AI/ML applications and microservices within the CLEAR AI platform