Quality Assurance Staff Engineer

Experience

• 5-8 years of relevant experience in the Artificial Intelligence industry

Qualification

• Bachelors or Masters degree in Engineering or Technology (B.Tech/M.Tech) with a focus on Computer Science, Artificial Intelligence, or related field.

Degree in Computer Science or a related field.

Behavioural Skills

• Excellent leadership and communication skills with the ability to collaborate effectively across multidisciplinary teams.
• Strong analytical and problem-solving capabilities, with a keen attention to detail.
• Adaptability and resilience in a fast-paced, dynamic AI environment.

Technical Skills

• Proven expertise in AI/ML Application QA, including testing of algorithms, models, and data processing pipelines.
• Advanced knowledge of Data & Analytics tools and methodologies, with hands-on experience in data validation and quality assurance processes.
• Familiarity with AI testing frameworks, tools, and techniques, such as TensorFlow, PyTorch, and MLflow.

Non-Negotiable Skills

• AI/ML Application QA
• Data & Analytics
• Quality Assurance Strategies
• Excellent command on Azure Board , JIRA, Charles , Jenkins , Selenium , APPIUM , Rest assured , Cucumber , BDD frameworks ,TestNG and Protractor frameworks, Katalon Studio , Postman , JMeter , GIT , SoapUI , Rest API.

1. As a QA Manager in the field of Artificial Intelligence, your responsibilities will include:
2. Developing and implementing comprehensive QA strategies for AI/ML applications, ensuring the highest standards of quality and performance.
3. Designing and executing test plans to validate AI algorithms, models, and data analytics processes.
4. Collaborating with cross-functional teams to identify and address quality-related issues throughout the AI product development lifecycle.
5. Establishing and maintaining QA metrics to track the effectiveness of testing activities and product quality.
6. Driving continuous improvement initiatives to enhance the efficiency and effectiveness of AI QA processes.
7. Providing leadership and mentorship to QA professionals, fostering a culture of excellence and innovation within the team
8. Extensive expertise in Web , Mobile App , API automation and Manual testing.
9. Should possess good business knowledge in more than one domain (Preferably AI , Data, HR, Ecommerce , BFSI etc )
10. Able to build/Set-up Automation frameworks from scratch and manage/maintain the automation framework and tools.
11. Excellent command on Azure Board , JIRA, Charles , Jenkins , Selenium , APPIUM , Rest assured , Cucumber , BDD frameworks ,TestNG and Protractor frameworks, Katalon Studio , Postman , JMeter , GIT , SoapUI , Rest API.
12. Possess strong programming skills (Java , Python). Should have experience in code reviews.
13. Proven experience as a Senior SDET or similar role, with a demonstrated history of leading large-scale automation projects.
14. Should have worked in Scale Agile methodology and have experience in continuous integration and deployment strategies
15. Experience with CI/CD tools (e.g., Jenkins, Azure DevOps)
16. Exposure to containerized deployment (e.g., Kubernetes / Docker) is a plus.
17. Strong understanding of Performance Testing concepts with proven track record of command on performance testing tools - Apache JMeter , LoadRunner etc.
18. Understanding and experience with building test solutions for real-time transactional services, REST services API, and container-based services.
19. High level of capacity to manage multiple projects and tasks concurrently in a fast-paced, dynamic environment.
20. Should be well aware of emerging technologies - AI , ML , LLM , AGI.
21. Detail-oriented approach to work, emphasizing accuracy and thoroughness in all tasks.
22. Excellent strategic and technical problem-solving skills.
23. A self-starter with a strong sense of individual motivation.
24. Exceptional communication and team collaboration skills.
25. Experience with agile methodologies is preferred.
26. Ability to translate complex technical concepts into understandable terms for non-technical stakeholders