Ai Qa Engineer (Genai And Ml Systems) 241831 Mer00048Yi

Job description

Tasks Job Description

AI QA Engineer (GenAI & ML Systems) We hiring an AI QA Engineer to own the quality, reliability and safety of our GenAI and ML-driven engineering applications. You will define how we test non-deterministic systems, from prompts and RAG pipelines to agentic workflows, and set the release bar for AI features used across Powertrain Engineering.

Key Responsibilities

• Design evaluation frameworks for LLM, RAG and agentic systems: accuracy, hallucination, consistency, latency and cost
• Build golden datasets, regression suites and automated eval pipelines integrated into CI/CD

Run red-teaming and adversarial tests

• prompt injection, jailbreaks, data leakage, bias and toxicity
• Validate retrieval quality, tool-calling and multi-step agent behavior
• Define quality gates and release criteria for AI features
• Monitor production drift and failure modes; lead root-cause analysis with AI engineers
• Report quality metrics and risks to engineering leadership Qualifications Required Qualifications :
• 4-8 years in QA/SDET, including 1-2+ years testing ML or GenAI systems
• Strong Python and test automation (pytest, API testing)
• Hands-on with LLM evaluation tools such as Ragas, DeepEval, promptfoo or LangSmith
• Working knowledge of LLM behavior, RAG architectures, embeddings and prompt engineering

Statistical thinking

• sampling, metric design, confidence, and the limits of LLM-as-judge
• CI/CD (GitHub Actions or Azure DevOps), Git and cloud fundamentals (Azure preferred)

Preferred Qualifications

• Experience with agent frameworks and MCP/tool integrations
• Observability tooling for tracing and drift monitoring

Exposure to engineering or automotive domains Who Qualifies

• Skeptical by default, precise, comfortable with non-deterministic outputs, a clear writer, and a close collaborator to AI engineers.

Experience

4-8 years Employment: Full-time