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Senior niche AI+QA role reduces applicant pool despite recognizable cybersecurity employer.
High domain bias: AI/LLM and cybersecurity testing expertise reduces cross-industry transferability.
Explicit 10+ years, staff seniority, and specific AI, cloud, and testing tool requirements make filtering stringent.
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Build and maintain scalable automation frameworks and continuous integration/delivery pipelines for AI, ML, and cybersecurity applications.
Ensure reliability, scalability, performance, and quality across distributed systems, cloud-native services, and large language model-driven applications.
Develop and implement validation pipelines for AI model behavior, including accuracy, latency, bias, hallucination detection, and regression testing.
10+ years of experience in delivering high-quality software solutions.
Experience with automation tools and frameworks for functional, load, and fuzz testing (e.g., Locust, CATS).
Experience deploying services on cloud platforms such as AWS, Azure, or GCP.
Work Experience Required: 10+ years. Other strict requirements: Background checks required.
Experienced in working with distributed systems and microservices architectures at scale.
Skilled in building and evolving automation frameworks and CI/CD pipelines supporting complex AI and cybersecurity applications.
Familiarity with validating AI/ML models and systems, including large language model evaluation and prompt engineering techniques.