AI Reliability QA Engineer

QualGent is seeking an AI Reliability QA Engineer to harden their autonomous AI systems for enterprise production environments. The role focuses on engineering reliability into AI-driven workflows, ensuring stability, reproducibility, and trust at scale.

Responsibilities:

• Deterministic AI Execution
• Identify and eliminate flakiness in AI-generated workflows
• Improve reproducibility across CI, staging, and production environments
• Design validation layers and guardrails for AI agent behavior
• Reduce regression escapes through structured reliability metrics
• Evaluate AI-generated test cases for correctness and coverage gaps
• Design stress-testing frameworks for AI workflows
• Improve system resilience under concurrency and load
• Define SLAs and reliability standards for autonomous execution
• Instrument execution traces across AI decision paths
• Build monitoring dashboards for reliability metrics
• Reduce time-to-diagnosis for complex failures
• Lead incident reviews focused on systemic improvements

Requirements:

• 2–10+ years of experience in QA, SDET, automation engineering, or reliability engineering
• Proven experience reducing flakiness in CI/CD pipelines
• Strong debugging capabilities across frontend, backend, and infrastructure layers
• Experience supporting and improving production releases
• Systems-level thinking with a focus on failure modes and edge cases
• Mobile testing expertise (iOS/Android, emulators, device farms)
• Experience with distributed systems
• Observability tooling experience (Datadog, Prometheus, OpenTelemetry, Sentry, etc.)
• Cloud infrastructure experience (AWS, GCP)
• Exposure to LLM-based or agent-driven systems