Head of Agentic Biology

Job title: Head of Agentic Biology Location: Cambridge, MA About the job The Computational and AI Strategy – R&D (CompAI) is a new function within Sanofi that brings together a multidisciplinary team of "bilinguals" — scientists and engineers with deep domain expertise and AI skills — across verticals including computational biology, molecular design, molecular engineering, safety, and manufacturing. CompAI is at the forefront of Sanofi's ambition to become the most AI-powered biopharma in the world, embedding cutting-edge computational capabilities directly into the heart of drug discovery and development. We are seeking a visionary, highly collaborative, and deeply technical leader to step into the role of Head of Agentic Biology within the Computational Biology group at CompAI. In an era where biology is rapidly becoming an information science, this forward-thinking role is designed to transform early discovery research using an AI-first mindset. Moving beyond traditional, reactive data analysis, the Head of Agentic Biology will collaboratively build an enterprise-scale computational ecosystem that accelerates end-to-end therapeutic area (TA) programs using an agentic approach. By closing the loop between automated wet-lab data capture and cutting-edge predictive modeling — including statistical methods, classical ML, language technologies, biological foundation models, and emerging agentic AI capabilities — this role will provide quantifiable insights that empower critical go/no-go portfolio decisions. A primary goal is advancing the discovery of novel targets with a high degree of success and extendable therapeutic opportunities, based on the analysis of large volumes of multi-modal disease data — including genetics, genomics, cellular, clinical, and pathological data — in close collaboration with Sanofi's therapeutic areas: immunology and inflammation, oncology, neuroscience, rare diseases, and ophthalmology, and in integration with CompAI verticals. Join the engine of Sanofi’s mission — where deep immunoscience meets bold, AI-powered research. In R&D, you’ll drive breakthroughs that could turn the impossible into possible for millions. About Sanofi We’re an R&D-driven, AI-powered biopharma company committed to improving people’s lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world. Together, we chase the miracles of science to improve people’s lives. Main Responsibilities: Acceleration of Discovery using Agentic Biology Lead the design and deployment of first-generation agentic bioinformatics workflows that automate end-to-end data capture, analysis, and insight generation across therapeutic programs. Drive the transition from reactive data analysis to proactive, predictive, and autonomous biological reasoning systems. Advance novel target discovery using multi-modal disease data including genetics, genomics, single-cell, proteomics, imaging, and clinical datasets. Leadership & Portfolio Impact Serve as a leader in bioinformatics, providing strategic direction aligned with Sanofi's R&D priorities across immunology, inflammation, oncology, neuroscience, rare diseases, and ophthalmology leveraging agentic technologies. Deliver quantifiable computational insights that directly inform go/no-go portfolio decisions and accelerate target validation. Translate computational discoveries into experimental target validation strategies with a focus on target biology, drug repurposing, and indication expansion. Present complex data and strategic recommendations to senior leadership with clarity and scientific rigor. Infrastructure & Technology Design, build, scale and transform existing bioinformatics infrastructure leveraging the modern bioinformatics stack, cloud-native architectures and agentic tooling. Oversee data modeling, data integration, pipeline development, AI/ML, DataOps, ModelOps, and cloud-native platforms to support Sanofi's AI-first vision. Lead the development of big data products including Genetic, Transcriptomic, and Proteomic Data Lakes in close collaboration with Digital/AI teams. Evaluate and onboard AI/ML vendors and optimize resource allocation across platforms and tools. Collaborative and AI-first mindset Champion collaborative ecosystem building with internal partners (e.g., Sanofi's Data Office, CompAI verticals, TAs and functions ) and external partners (vendors, CROs, academia). Integrate biological, clinical, and healthcare data using advanced tools and workflows across organizational boundaries. Apply agile principles to manage and deliver complex, multi-stakeholder programs. Bring a consultancy mindset and excellent cross-functional communication skills to drive alignment across R&D. Project Management, Leadership & Mentoring Lead, mentor, and coach a multidisciplinary team of scientists, data engineers, and ML engineers in a project-centric framework. Build and develop matrix and international teams with a culture of scientific excellence, innovation, and psychological safety. Foster a learning environment that keeps the team at the cutting edge of computational biology and AI. About you Basic Qualifications: PhD in AI, Machine Learning, Immunology, Mathematics, Physics, Biomedical Engineering, Computational Biology, Bioinformatics, or a related STEM field. 5+ years of experience in AI/ML required; experience in biotech, biopharmaceuticals, pharmaceuticals, or academia is preferred Familiarity with agentic AI frameworks and autonomous workflow orchestration. Hands-on experience with emerging AI for Science tools and platforms in biology, including Owkin K-Pro, Google Co-Scientist, Phylo (Biomni), Mithrl, EMET, PandaOmics (Insilico Medicine), NVIDIA BioNeMo Agent Toolkit, Claude Science (Anthropic), or other related agentic and foundation model-based tools shaping the next generation of computational drug discovery and therapeutics development. Familiarity with biological foundation models and their application in drug discovery, including protein language models (e.g., ESM, AlphaFold 3), genomic foundation models (e.g., Nucleotide Transformer, HyenaDNA, Evo), and multimoda