Principal Agentic Workflow & AI Engineer, Biologics Discovery

Principal Agentic Workflow & AI Engineer

Johnson & Johnson Innovative Medicine is seeking a Principal Agentic Workflow & AI Engineer to help build the agentic layer of our Biologics Discovery data engine. This is an opportunity to be one of the early, senior experts shaping how agentic AI workflows automate secondary data processing, orchestrate analyses, and connect experimental outputs to models and decisions across the DMTL (design-make-test-learn) cycle.

You will work at the intersection of scientific experimentation, data pipelines, AI systems, and lab automation.

This position will be located at one of our office locations in either Spring House, PA (preferred), Titusville, NJ, or Raritan, NJ. (No remote option.)

Why this role matters:
Getting biologics data to flow reliably through our systems is a critical, often underestimated challenge, and there is significant opportunity to automate secondary analysis. This role brings agentic AI and intelligent automation to compress cycle time, reduce manual intervention, and improve reproducibility - transforming today's hands-on processes into scalable, connected, intelligent discovery workflows. It is a strategically visible Principal-level role, central to our next-generation discovery automation.

Why This Role Is Unique

This is a rare chance to architect how scientific and physical AI come together to steer design and execution in the lab - not just automating steps but building a next-generation discovery engine in a large pharma setting. As a Principal individual contributor, your work will be among the most visible and influential on the team and will directly accelerate how tomorrow's therapies are discovered.

Position Summary

As a Principal Agentic Workflow & AI Engineer, you will design and build agentic workflows and orchestration that own the scientific data analysis and secondary processing logic our team delivers. You will translate scientific priorities into automation and AI roadmaps, and build real-time pipelines connecting automation software, data stores, models, and compute.

You will partner across Discovery, Data Science, In Silico Discovery (ISD), our Enterprise Generative AI team, and our data-infrastructure and lab-automation teams to enable closed-loop feedback so that each experimental cycle improves downstream models and decisions - timed to lab-automation readiness as new automation infrastructure comes online. You will also set technical direction and mentor other team members.

Key Responsibilities

• Agentic Orchestration & Integration
• AI-Driven Scientific Learning
• Technical Leadership

Qualifications

• Required
• Preferred