This role pays less than
51%
of similar roles. Most pay
$182,812–$260,250
— the shaded band above.
At the midpoint, this role pays about
$218k
versus about
$222k
for comparable roles.
Based on 240 similar postings.
Employer
About Sanofi
Sanofi is a French global R&D-driven and AI-powered biopharmaceutical company focused on human health through specialized medicine, vaccines, and consumer healthcare.
The Head of Agentic Biology joins the Computational and AI Strategy – R&D team to lead the design and deployment of agentic bioinformatics workflows that automate data capture, analysis, and insight generation across therapeutic programs. This role focuses on transitioning from reactive data analysis to proactive, autonomous biological reasoning systems to accelerate target discovery. The successful candidate will build an enterprise-scale computational ecosystem using a modern bioinformatics stack, cloud-native architectures, and agentic tools. Key technologies include statistical methods, classical machine learning, language models, and biological foundation models like AlphaFold 3 or Nucleotide Transformer. The role involves analyzing multi-modal disease data—including genetics, proteomics, and clinical datasets—to inform go/no-go decisions in areas such as oncology, neuroscience, and immunology. You will manage a multidisciplinary team of scientists and engineers to solve complex drug discovery challenges through an AI-first approach.
LLMs
Agent Frameworks
RAG
Vector Databases
Python
Prompt Engineering
Machine Learning
Deep Learning
Cloud-native Development
APIs
Data Science
Statistical Analysis
Time Series Analysis
Data Visualization
Observability
Artificial Intelligence
Machine Learning
Python
R
Generative AI
Large Language Models
Retrieval-Augmented Generation
Agentic Workflows
Bioinformatics
Cloud Computing
Containers
Version Control
Data Science
Statistical Computing
LLM
LangChain
AutoGen
CrewAI
Retrieval Systems
CI/CD
Jenkins
GitLab CI
Software Development Lifecycle
Dynamic Analysis
Performance Engineering
Data Governance
Model Risk Management