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Niche AI-testing skills reduce applicant pool, but metro Bangalore and notable employer create medium competition.
Highly specialized LLM and AI testing skills limit transferability across industries.
Mandatory 7+ years, specific AI testing, SDET experience, and tooling requirements make filters highly strict.
Design and scale automated validation frameworks for AI/ML models, LLM-based applications, and agentic systems to meet enterprise standards for quality, reliability, safety, and compliance.
Develop and maintain comprehensive test suites covering unit, integration, E2E, functional, regression, performance, and safety testing across AI systems, including handling non-deterministic outputs and multi-step agent decisions.
Collaborate cross-functionally to define quality gates, manage evaluation systems, automate testing in CI/CD pipelines, track quality KPIs, and support audit and compliance readiness.
7+ years of experience in QA, SDET, or test automation engineering with hands-on experience in AI/ML or LLM-based system testing.
Proficiency in Python programming and test automation frameworks (e.g., PyTest, Playwright, Selenium).
Experience with CI/CD tools (GitHub Actions, Jenkins, GitLab CI), cloud platforms (AWS, Azure, GCP), and container technologies (Docker, Kubernetes).
Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field.
Experienced in owning end-to-end AI test strategy, architecture, and delivery of scalable validation pipelines for production AI systems.
Skilled in testing agentic workflows, RAG pipelines, and applying advanced AI testing techniques including non-deterministic testing and AI safety validation.
Capable of working in enterprise or regulated environments with knowledge of compliance standards and integration of observability, monitoring, and audit readiness in AI system testing.