Job Description

Job Title: Quality Engineering Solutions Architect (AI & Gen AI Focus)

Location: Bangalore, India

Department: Quality Assurance / Engineering

Key Responsibilities:

- Framework Design: Architect and implement scalable testing frameworks for automation, performance, and data validation focused on AI and Generative AI applications.

- Strategy Development: Collaborate with product managers, data scientists, and software engineers to define quality objectives and develop comprehensive testing strategies that align with product goals.

- Automation Implementation: Lead the creation of automation scripts and tools to enhance testing efficiency and effectiveness, utilizing relevant technologies and programming languages.

- Performance Testing: Develop and execute performance testing strategies to assess the scalability, reliability, and responsiveness of AI-based applications under various load conditions.

- Data Quality Assurance: Establish data testing frameworks that validate data integrity, accuracy, and performance in AI models and pipelines, ensuring compliance with industry standards and best practices.

- Continuous Improvement: Identify areas for improvement in the quality assurance processes and propose innovative solutions that drive operational excellence.

- Collaboration: Work closely with cross-functional teams to facilitate communication, understanding, and ownership of quality practices across the organization.

- Mentorship: Provide guidance and mentorship to junior QA engineers, fostering a culture of quality and continuous learning.

- Documentation: Create and maintain comprehensive documentation related to testing strategies, frameworks, and processes.

Qualifications:

- Education: Bachelor’s degree in Computer Science, Engineering, or a related field; advanced degree preferred.

- Experience: 18+ years of experience in software quality engineering with a focus on automation, performance testing, and data quality assurance.

- Technical Skills:

- Proficient in programming languages such as Python, Java, or C#.

- Extensive experience with test automation tools (e.g., Selenium, JUnit, TestNG).

- Knowledge of performance testing tools (e.g., JMeter, LoadRunner).

- Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch) is a plus.

- Strong understanding of data validation techniques and tools.

- Strong Analytical Skills: Demonstrated ability to analyze complex systems and identify areas for improvement.

- Leadership Abilities: Proven track record of leading quality engineering initiatives and cross-functional projects.

- Excellent Communication: Strong verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

- Problem-Solving Mindset: A proactive approach to identifying challenges and developing effective solutions.

- Experience with cloud technologies and platforms (e.g., AWS, Azure, Google Cloud).

- Familiarity with CI/CD pipelines and DevOps practices.

- Knowledge of compliance and regulatory standards related to AI and data testing.