Sr Engineer – GenAI Quality Assurance

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com.

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

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/

• →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

• 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

• 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

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