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Senior, specialized QA role reduces applicant volume, but strong employer brand and metro hiring keep competition medium.
Specialized AI/ML testing within cybersecurity and cloud reduces transferability; high background sensitivity.
Explicit 10+ years, specific AI/ML, cloud, CI/CD, and testing-tool requirements make shortlisting highly strict.
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Develop and maintain scalable automated testing frameworks and CI/CD pipelines for AI, machine learning, and cybersecurity distributed systems and cloud-native services.
Architect and execute validation pipelines for large language models focusing on accuracy, latency, bias, toxicity, and reliability.
Lead testing strategy reviews and collaborate closely with software engineering teams to improve software quality, reliability, and deployment confidence.
10+ years of experience delivering high-quality software solutions.
Strong expertise in automation frameworks, continuous integration/delivery pipelines, and functional, load, and fuzz testing tools like Locust and CATS.
Experience deploying services on cloud platforms such as AWS, Azure, or Google Cloud Platform.
Work Experience Required: 10+ years in software quality engineering and automation specifically in distributed systems and microservices architectures.
Experienced working at the intersection of AI, ML, big data, and cybersecurity with hands-on knowledge of AI/ML testing techniques and frameworks.
Demonstrated ability to build scalable, reliable automated test infrastructures supporting high-throughput distributed systems.
Proven collaborator capable of working across multiple engineering teams to deliver resilient, high-performance systems and to proactively identify issues pre-production.