05 Feb
CareerXperts Consulting
Bengaluru
As AI capabilities accelerate, every customer-touching function within the enterprise is being redefined. The future lies in the seamless connection between people, systems, and data—enabling more intuitive, human-centric experiences for both customers and employees.
Job Description
Key Responsibilities:
Own and drive the QA vision and roadmap for AI-driven and SaaS platforms, continuously improving automation depth, test coverage, and release confidence.
Architect and deliver scalable test automation solutions across APIs, UI layers, and data validation, leveraging modern AI-assisted automation techniques.
Collaborate closely with Data Science and Engineering teams to validate AI/ML pipelines, analytics workflows, and model integrations in production-grade environments.
Lead performance, security, and regression testing initiatives to ensure platform reliability, resilience, and scalability at enterprise scale.
Conduct root cause analysis and quality trend reviews to identify systemic gaps and propose targeted automation or process improvements.
Maintain comprehensive QA documentation, including test strategies, release artifacts, and best practices using tools like Jira and Confluence, aligned with Agile/SAFe methodologies.
Ensure comprehensive end-to-end test coverage across microservices, APIs, mobile, and web applications deployed in multi-tenant cloud environments.
Qualifications
Bachelor’s degree in Computer Science, Engineering, or a related field.
4+ years of experience in Software Quality Assurance with a strong emphasis on test automation.
Advanced proficiency in at least one programming language such as Java, Python, JavaScript, or TypeScript.
Solid ability to analyze complex features, author high-quality test cases, and develop automation scripts with meaningful assertions and validations.
Proven experience designing, building, and maintaining custom automation frameworks.
Hands-on experience testing distributed systems for end-to-end scenarios, long-running stability, reliability, migration, and performance.
Experience defining and executing AI testing strategies, including validation of foundation models, prompt engineering, fine-tuning, RAG pipelines, and Generative AI frameworks (e.g., LangChain, Guidance).
Solid understanding of CI/CD pipelines and tools such as Jenkins, GitHub Actions, GitLab CI, or CircleCI.
Demonstrated ability to reason about complex, distributed architectures and create effective test strategies for them.
Strong analytical thinking, debugging skills, and problem-solving capabilities.
Preferred Skills
Exposure to microservices-based architectures and associated testing approaches.
Experience with performance and load testing tools such as JMeter, Gatling, or k6.
Hands-on experience with cloud platforms (AWS, GCP, or Azure); familiarity with at least one is preferred.
Prior experience working in Agile or Scrum-based delivery models.
Experience mentoring or leading QA engineers.
Background in testing data-intensive or data-driven applications.
Write to [email protected]
📌 Lead SDET - Distributed Systems - US Based AI Enterprise Platform (Bengaluru)
🏢 CareerXperts Consulting
📍 Bengaluru
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