AI QA Engineer (GenAI & ML Systems)
Full Job Posting
Requirements
- 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)
- Experience with agent frameworks and MCP/tool integrations
- Observability tooling for tracing and drift monitoring
- Exposure to engineering or automotive domains
- 4-8 years
Full Job Posting
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
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
Job Details Group: Mercedes-Benz Group AG Organization: Mercedes-Benz Research and Development India Private Limited Primary Location: India-Karnataka-Bangalore Work Locations: Mercedes-Benz Research & Development India, Embassy Crest, 'Embassy Crest' Plot No 5,, EPIP Zone, Phase 1,, 560 066
About Mercedes-Benz Research and Development India Private Limited
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