Principal Scientist, Scientific Workflows & Agentic Cheminformatics

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and Med Tech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.

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Data Analytics & Computational Sciences

Data Science

Scientific/Technology

Cambridge, Massachusetts, United States of America;
Spring House, Pennsylvania, United States of America;
Turnhout, Antwerp, Belgium

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow. Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way. Learn more at

Johnson & Johnson Innovative Medicine is recruiting for a Principal Scientist, Scientific Workflows & Agentic Cheminformatics to join our In Silico Drug Discovery team. This position will be located in either Spring House, PA; or Cambridge, MA and may require some travel as needed (no remote option). Consideration may be given for candidates located in Beerse, Belgium. Please note that this role is available across multiple countries and may be posted under different requisition numbers to comply with local requirements.

While you are welcome to apply to any or all of the postings, we recommend focusing on the specific country(s) that align with your preferred location(s): USA

- Requisition Number: R-102947 Belgium
- Requisition Number: R-104669

The Principal Scientist will lead the identification, scientific design, prototyping, and validation of agent-enabled workflows that address high-value discovery questions across multiple use cases or discovery areas. This individual will also establish the scientific evidence, adoption model, and partnerships needed to advance promising concepts into broadly used capabilities.

• Build trusted partnerships with medicinal chemists, CADD scientists, biologists, DMPK scientists, data scientists, and scientific leaders to understand decision workflows and identify opportunities with impact across projects or discovery areas.
• Shape and prioritize a portfolio of scientific questions and decision points where agentic approaches can bring together data, models, and expert knowledge to improve the quality or speed of discovery.
• Define robust and reusable approaches for translating complex scientific questions into workflows that make evidence, assumptions, decisions, and points requiring expert judgment explicit.
• Design scientifically meaningful use cases, reference datasets, and success criteria that enable rigorous evaluation.
• Evaluate agent behavior and outputs for scientific validity, reproducibility, uncertainty, appropriate tool use, robustness across scenarios, and relevance to discovery decisions.
• Capture the scientific insights gained from early applications and use them to define which approaches merit further development and broader adoption.
• Develop and test agentic prototypes in realistic discovery settings, combining scientific expertise with relevant data, predictive models, computational or laboratory methods, and tools that agents can select and coordinate to address a scientific objective.
• Provide scientific and technical leadership across a portfolio of agentic prototypes, set priorities and success measures, guide trade‑off decisions, and ensure that the work addresses meaningful discovery needs and delivers measurable value.
• Drive broader adoption of agentic capabilities by integrating them into familiar scientific environments, establishing effective patterns for human-agent collaboration, and building communities of practice across discovery functions.
• Lead the scientific design, prototyping, and validation of agent-enabled discovery workflows, and partner with data science and platform engineering teams from an early stage on the underlying AI architecture, production implementation, security, and sustained operation.
• Translate scientific requirements and evidence into reusable capabilities that align…