GenAI QA Engineer — Build Reliable AI Pipelines

Johnson & Johnson Innovative Medicine; Cornellà de Llobregat; Híbrido; EUR 70.000 - 110.000; Jornada completa

Descripción de la vacante

Johnson & Johnson Innovative Medicine is seeking a Senior Engineer – GenAI Quality Assurance. The role can be based in Madrid or Barcelona with a hybrid work model.

You will design and implement QA strategies for GenAI systems, validate model behavior, and collaborate with data scientists to ensure robust, reliable AI products across the lifecycle. Ideal candidates have 3+ years in software or QA, advanced Python skills, and hands-on experience with LLM-based systems and cloud platforms such as

Formación

• 3+ years as software engineer or QA in production systems, preferably in GenAI.
• Advanced Python skills and strong software engineering background.
• Experience with LLM-based systems and GenAI validation workflows.
• Familiarity with RAG and graph frameworks.

Responsabilidades

• Design and implement automated and manual QA strategies for GenAI systems.
• Build regression tests and evaluation pipelines for accuracy and robustness.
• Validate prompt logic, model behavior, and evaluation metrics.
• Execute tests, debug pipelines, and support deployment of GenAI products.
• Lead design reviews, promote reliability of GenAI applications.
• Collaborate with data scientists and developers to embed testing checkpoints.

Conocimientos

Python

GenAI QA

LLM systems

Test automation

Cloud platforms

Herramientas

AWS Bedrock

Azure Foundry

GCP Gemini

Git

Jenkins

Descripción del empleo

Johnson & Johnson Innovative Medicine is seeking a Senior Engineer – GenAI Quality Assurance. The role can be based in Madrid or Barcelona with a hybrid work model.

You will design and implement QA strategies for GenAI systems, validate model behavior, and collaborate with data scientists to ensure robust, reliable AI products across the lifecycle. Ideal candidates have 3+ years in software or QA, advanced Python skills, and hands-on experience with LLM-based systems and cloud platforms such as