Senior 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 MedTech, 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. Learn more at jnj.com.

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

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 MedTech, 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.

We seeking for a talented computational Senior Scientist in Cheminformatics development, joining our cutting-edge In Silico Discovery department within Therapeutics Discovery at J&J.
A discovery scientist who applies cheminformatics and emerging agentic approaches to important scientific questions, develops and validates new workflows, and helps make useful capabilities accessible to scientists through familiar discovery environments.

The primary location for this role is Belgium.

Spain and the East & West coast of America will be considered also.

Design, prototype, and validate agent-enabled workflows for defined high-value discovery questions or use cases. Generate the scientific evidence, user feedback, and implementation requirements needed to advance successful concepts toward broader use in partnership with project, data science, and platform teams.

• →Build trusted partnerships with medicinal chemists, In Silico Discovery (ISD) / CADD scientists, biologists, DMPK scientists, and data scientists to understand decision workflows and identify valuable opportunities within projects or defined discovery areas.
• →Translate complex scientific questions into well-defined workflows that make evidence, assumptions, decisions, and points requiring expert judgment explicit, and contribute reusable approaches where appropriate.
• →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.
• →Take scientific and technical ownership of defined agentic prototypes or workstreams, set fit-for-purpose success measures, make informed trade-offs, and ensure that the work addresses meaningful discovery needs and delivers measurable value.
• →Support adoption of agentic capabilities by integrating them into familiar scientific environments and working directly with users through project partnerships, training, and feedback.
• →Lead the scientific design, prototyping, and validation of assigned agent-enabled discovery workflows, and collaborate with data science and platform engineering teams from an early stage by contributing scientific requirements, evidence, and user feedback for production implementation, security, and sustained operation. Help translate successful project solutions into reusable capabilities aligned with shared architectures.

• PhD or equivalent substantial experience in cheminformatics, computational chemistry, medicinal chemistry, chemical biology, or a related discipline, with strong scientific expertise relevant to drug discovery.
• Strong understanding of compound design and predictive models with the ability to connect scientific needs across disciplines within project or capability teams.
• Strong Python programming skills and experience developing automated workflows, pipelines, or scientific applications to explore scientific questions and create practical proof-of-concept solutions.
• Hands-on experience using AI-assisted development approaches to build reliable scientific software or automated workflows
• Demonstrated ability to work independently in an emerging area, translate scientific needs into practical solutions, and collaborate effectively across scientific, data science, and technology teams.
• Ability to travel domestically and internationally up to 10% of the time.

• Experience designing and evaluating end-to-end agent-enabled scientific workflows or multi-agent solutions is preferred.
• Familiarity with workflow orchestration and sound software development practices, including version control, testing, and continuous integration and delivery.
• Strong knowledge of and hands-on experience with public and commercial bioactivity and chemogenomics databases