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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Scientist - Generative AI for Workflow - **Company:** Johnson & Johnson, S.a. - **Location:** Madrid, Spain - **Salary:** €55,400.0 - €87,860.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Bioinformatics, Computer Literacy, Data Visualization, Information Theory, Python (Programming Language), Performance Tuning, Tensorflow, Flexi (Photoshop Plugin), Cloud Platform System, Pytorch, Large Language Models, Multi-Agent Systems, Deep Learning, Generative AI, Git, Information Technology - **Published:** September 18, 2026 - **Apply:** https://www.adzuna.es/contact-us.html ## About the Role + Master's degree in AI/ML, Computer Science, Engineering, Bioinformatics, or related field with 2+ years of hands-on experience in GenAI Science/Engineering. + Hands-on experience with multi-agent frameworks such as LangGraph, DSPy, memO, or similar architectures. + Strong proficiency in Python and modern deep-learning frameworks (PyTorch, TensorFlow). + Experience building retrieval-augmented generation (RAG) systems, including chunking, embeddings, vector databases, and reranking. + Knowledge of advanced mathematical concepts such as uncertainty quantification, probabilistic modelling, or information theory. + Experience implementing structured generation, schema enforcement, and model/tool orchestration for complex workflows. + Positive, motivated, collaborative approach with the ability to work independently and within a multidisciplinary environment. Preferred Qualifications + Understanding of the drug development pipeline, regulatory submissions, and biological or chemical data types. + Familiarity with scientific literature analysis, knowledge extraction, and structured content generation. + Experience in QC systems, verification agents, or regulatory document automation. + Experience fine-tuning LLMs for specialised domains and deploying AI systems in cloud environments (AWS or Azure). + Strong understanding of statistical validation methods for AI-driven workflows. + Experience with Git-based development and CI/CD pipelines. Our Values Integrity, innovation, collaboration, and responsibility are at the heart of everything we do. We foster an inclusive environment where diverse perspectives drive breakthrough solutions. Johnson & Johnson is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, sex, sexual orientation, gender identity, age, national origin, or protected veteran status and will not be discriminated against based on disability. Required Skills: Preferred Skills: Advanced Analytics, Consulting, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Digital Fluency, Econometric Models, Mentorship, Strategic Thinking, Tactical Planning, Technical Credibility ## Description As a Senior Scientist in the Workflow, Applications and Plug-ins team within Data, Data Science and AI Org, you will lead the technical and product evolution of reusable GenAI-enabled content-authoring workflows across R&D, spanning therapeutic-area document generation, regulatory authoring, scientific content workflows and future integration with broader dossier and submission processes. The role will help establish a reusable document-authoring capability on an internally built Agentic Platform rather than creating isolated solutions for individual document types., + Lead technical strategy and implementation of GenAI-enabled document-authoring workflows. + Translate individual document workflows into reusable authoring capabilities and identify document-specific versus enterprise-common logic. + Develop roadmap and requirements across multiple document classes and R&D functions. + Establish patterns for evidence retrieval, grounding, drafting, citation, structured content, review and revision. + Partner with Data teams to define source-data requirements and enterprise data connectivity. + Partner with Evaluation & Quality to establish content-quality, faithfulness, traceability and regulatory-readiness evaluation. + Integrate reusable QC/content-review capabilities into authoring workflows. + Evaluate where external vendor capabilities can be consumed as modular services rather than forcing end-to-end vendor architectures. + Work with Foundation Platform Team to identify reusable plugin and platform requirements generated from document-authoring use cases. + Provide technical leadership to engineers, contractors, domain SMEs and federated Data Science partners. + Drive workflows from prototype toward scalable enterprise capability. ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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