Role Overview

Lead QA strategy and test automation for AI/ML systems, LLMs, RAG pipelines, and autonomous agents, ensuring accuracy, robustness, security, performance, and regulatory compliance.

Key Responsibilities

- Define AI/ML testing strategies, quality KPIs, and regression frameworks.

- Validate LLM/RAG outputs, hallucinations, retrieval accuracy, bias, and fairness.

- Perform prompt-injection testing, red teaming, and security assessments.

- Automate tests using Python and validate AI APIs, performance, and scalability.

- Test model drift, fallback mechanisms, and retrained models.

- Maintain audit-ready evidence and mentor junior QA engineers.

Required Skills

- AI/ML, LLM, RAG, and agent testing.

- Python, test automation, and API testing.

- Prompt injection, red teaming, and AI security testing.

- Performance testing: latency, throughput, and concurrency.

- Model accuracy, robustness, bias/fairness, and explainability.

- Data privacy, AI ethics, and regulatory compliance.

Nice to Have:

Insurance domain experience, synthetic data generation, multi-agent benchmarking, and model drift testing.

📌 Quality Engineer Lead Expert (AI/ML & LLM QA) (Barcelona)
🏢 Ubique Systems
📍 Barcelona