> Markdown version of [/jobs/ext/2935322-senior-scientist-generative-ai-for-workflow-applications-and-plug-ins](https://www.wearedevelopers.com/jobs/ext/2935322-senior-scientist-generative-ai-for-workflow-applications-and-plug-ins). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Scientist - Generative AI for Workflow, Applications and Plug-ins - **Company:** J&J Family of Companies - **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), Tensorflow, Flexi (Photoshop Plugin), Cloud Platform System, Pytorch, Large Language Models, Multi-Agent Systems, Deep Learning, Generative AI, Git, Information Technology - **Published:** September 16, 2026 - **Apply:** https://dejobs.org/x/x/6059177F65F649C398C07DFCF8F3A27C/job/ ## 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., * 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., 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 * 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 - [Building Products in the era of GenAI](https://www.wearedevelopers.com/videos/827-building-products-in-the-era-of-genai) - [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. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Should we build Generative AI into our existing software?](https://www.wearedevelopers.com/videos/1129-should-we-build-generative-ai-into-our-existing-software) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Got AI ideas but no money? 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