Overview

In this on-site role in Barcelona, you will shape agentic AI for clinical trial design, execution, and learning. You’ll work within a hands-on clinical AI group that partners with clinical and R&D; teams to move ideas from prototype to production. You’ll develop production-grade Python systems, data pipelines, and retrieval tools while ensuring provenance and safety. You’ll design disciplined experiments to quantify impact and translate findings into robust, scalable capabilities. You will contribute to an ambitious mission to accelerate patient access to effective medicines through trustworthy AI-enabled workflows.

Responsabilidades

- Design and deliver LLM-driven, agentic workflows for trial planning, conduct, monitoring, review, and reporting to improve speed, quality, and evidence transparency
- Write production-quality Python and SQL; build services, data pipelines, retrieval systems, tool integrations, structured-output components, and automated tests to meet reliability, latency, and cost targets
- Integrate structured and unstructured clinical sources with provenance, access controls, data contracts; implement verification, citations, uncertainty handling, and human-in-the-loop review
- Build reproducible experiments and evaluation datasets; select metrics; perform error analysis; compare models, retrieval strategies, and orchestration patterns; translate findings into concrete improvements with release evidence
- Co-create solutions with CRAs, clinical scientists, medical monitors, and operations teams; iterate through rapid prototyping and user feedback; contribute to design reviews, code reviews, documentation, risk assessments,



and reusable components
- Track advances in agentic AI, clinical NLP, multimodal models, evaluation, and responsible AI; reproduce promising methods; present results to specialists and non-specialists; contribute to internal standards and external scientific engagement

Requisitos principales

- PhD in Computer Science, Machine Learning, Biomedical Informatics, Computational Biology, Statistics, or related quantitative field; or a master’s with equivalent applied research and engineering experience
- Strong hands-on Python programming and working knowledge of SQL, software testing, version control, APIs, and reproducible development practices
- 1 to 3 years post-PhD (or master’s-level equivalent) experience building applied ML, NLP, generative-AI, or agentic systems beyond notebooks
- Understanding of modern language-model techniques, retrieval-augmented generation, embeddings, tool use, structured generation, and evaluation
- Ability to design controlled experiments, select meaningful metrics, perform error analysis, and communicate uncertainty
- Experience with complex, heterogeneous, or imperfect data and tracing outputs to sources
- Curiosity about clinical development and ability to learn domain workflows through literature, data, and collaboration with SMEs
- Clear written and verbal communication and a collaborative approach with product, engineering, clinical, and quality colleagues
- Commitment to reproducibility, responsible AI, patient privacy, and higher evidentiary standards for clinical applications

- collaborative approach
- curiosity
- clear communication
- Python
- SQL
- APIs

📌 Senior Scientist, Clinical Agentic AI (Barcelona)
🏢 AstraZeneca
📍 Barcelona