Senior GenAI Quality Assurance Engineer

Job Function

R&D Product Development

Job Sub Function

R&D Machine Learning

Job Category

Scientific/Technology

All Job Posting Locations

Cornellà de Llobregat, Barcelona, Spain, Madrid, Spain

Job Description

Johnson & Johnson Innovative Medicine R&D Data Science and Digital Health is recruiting for a Senior Engineer - GenAI Quality Assurance. This role can be based in Madrid or Barcelona. Hybrid working.

J&J Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, immunology, neuroscience, cardiopulmonary and specialty ophthalmology. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market - from patients to practitioners and from clinics to hospitals. To learn more about Johnson & Johnson Innovative Medicine visit https://innovativemedicine.jnj.com/

Description: We're hiring a professional who specializes in designing, testing, and refining complex GenAI applications, primarily in scientific or ML-driven environments. You'll be responsible for validating, stress-testing, and improving Gen-AI powered products (pipelines and AI-assisted workflows) across the product lifecycle - from pre-deployment validation to post-release monitoring.

Key Responsibilities

• Design and implement automated and manual QA strategies for GenAI systems
• Build regression tests, generate synthetic test data, build test harnesses and evaluation pipelines for accuracy, grounding, robustness, safety
• Validate prompt logic, model behavior and evaluation metrics
• Execute tests and debug pipelines
• Support deployment of GenAI products
• Lead system design reviews, advocating best practices for architecture and reliability of GenAI applications
• Collaborate closely with data scientists and developers to embed testing and quality checkpoints
• Establish testing standards and workflows for continuous integration and deployment
• Conduct code reviews with a focus on design, testability, and maintainability
• Document system design decisions, test cases, and best practices
• Close collaboration with domain experts and stakeholders to validate developed solutions

Technical Skills & Experience Needed

• Strong software engineering background with QA ownership
• Familiarity with RAG & Graph frameworks
• 3+ years of experience as a software engineer (preferably 5), or QA engineer in production systems, preferably including at least 1 year experience in GenAI systems
• Advanced Python skills
• Experience working with LLM-based systems in real environments
• Hands-on experience with:

• LLM APIs
  • AWS Bedrock (Anthropic & OSS)
  • Azure Foundry (OpenAI)
  • GCP (Gemini)
• Cloud platforms (AWS, Azure, GCP)
• Proven ability to implement test frameworks for GenAI applications

• Knowledge of API testing, data validation, and data pipeline testing
• Experience with version control (Git)
• Experience with building and deploying AI/ML products through the full product lifecycle
• Good understanding of scientific computing and ML frameworks
• Solid understanding of safety, bias, and failure modes of GenAI systems
• Comfortable working in a relatively fast-moving environment where priorities may shift and initiative is valued
• Proactive problem-solver who can anticipate needs and find solutions
• Comfortable working independently, but also a strong team player

Nice-to-Have

• Experience with Jenkins, Sonarqube
• Monitoring and observability tools (Prometheus, Grafana etc)
• Devops experience (docker, jenkins)
• Experience deploying GenAI services to production at scale
• Exposure to ML Ops or production ML systems

#LI-GR

#LI-Hybrid

#JRDDS
#JNJDataScience
#JRD

Required Skills

Large Language Models (LLMs), Microsoft Foundry, OpenAI, Python (Programming Language), Software Quality Assurance (SQA)

Preferred Skills

Artificial Intelligence (AI), Coaching, Cognitive Computing, Critical Thinking, Cross-Functional Collaboration, Curious Mindset, Data Structures, Distributed Computing, Emerging Technologies, Human-Computer Relationships, Machine Learning (ML), Persistence and Tenacity, Program Management, Research and Development, SAP Product Lifecycle Management, Scripting Languages, Technologically Savvy