Lead / Senior QA Engineer – Agentic AI Systems

Pro Talent Crafter is seeking a highly skilled QA professional to build and scale a next-generation Agentic AI Quality Engineering function. This role focuses on validating autonomous AI systems, designing evaluation frameworks, and ensuring high-quality outputs across multiple AI-driven products.

Responsibilities:

• Design and scale an agentic QA model for autonomous AI systems
• Move QA from human-driven validation to AI-led evaluation and continuous quality monitoring
• Establish best practices for testing AI agents across lifecycle stages
• Own QA for 3 core AI products: AI Contact Center solutions, AI Chat & Form-based interaction systems, AI Assistants (autonomous / semi-autonomous agents)
• Define quality benchmarks, SLAs, and success metrics for each product
• Proactively identify quality gaps ahead of customer impact
• Define and track performance outputs for agentic systems (accuracy, latency, resolution quality, hallucination rate, etc.)
• Build frameworks for: Evals & graders (LLM evaluation pipelines), Output scoring and benchmarking, Continuous feedback loops
• Leverage tools like Langfuse for: LLM observability and tracing, Prompt monitoring and performance analysis, Debugging agent behavior in production
• Analyze: Downstream issues, Production tickets, Failure patterns
• Build and scale automation across: Regression testing, Smoke testing, End-to-end agent workflows
• Develop and maintain Playwright-based automation scripts
• Integrate QA into CI/CD pipelines for continuous validation
• Design testing approaches for: Multi-step agent workflows, Context retention and reasoning, Tool usage by agents
• Work with orchestration frameworks like Temporal to: Validate long-running workflows, Test retries, state transitions, and failure handling in agent pipelines
• Account for non-deterministic behavior in AI systems
• Invest additional effort in agentic validation, recognizing higher complexity vs traditional QA
• Define frameworks to predict and prevent failures before customer exposure
• Continuously improve QA processes using AI and automation
• Partner with Product, Engineering, and AI teams to improve system quality

Requirements:

• 5–10+ years in QA / Quality Engineering, with strong automation experience
• Hands-on experience with test automation tools (Playwright preferred)
• API and system testing
• Strong understanding of AI/ML systems (LLMs, conversational AI preferred)
• Evaluation frameworks and benchmarking
• Experience with Temporal (workflow orchestration, stateful systems testing)
• Langfuse (LLM observability, tracing, and evaluation)
• Experience in building QA frameworks from scratch
• Working with production data, logs, and issue triaging
• Experience with LLM eval frameworks, prompt testing, or AI red-teaming
• Familiarity with agentic architectures / autonomous systems
• Exposure to observability and analytics platforms