Senior Agentic Workflow Engineer (AI)

Location: Onsite at an office in Spring House, PA; Titusville, NJ; Raritan, NJ; Cambridge, MA, USA; or Madrid, Spain. No remote option.

Salary: $109,000–$174,800 annual base pay for candidates hired in the United States, plus eligibility for an annual performance bonus. Compensation and benefits for candidates hired outside the United States follow the local market.

Company

Johnson & Johnson develops healthcare, Innovative Medicine, and MedTech solutions focused on preventing, treating, and curing complex diseases.

What you will do

• Build and continuously improve agentic workflows that automate secondary analysis for biologics discovery assays.
• Develop near-real-time pipelines connecting laboratory automation software, data stores, models, and compute environments.
• Implement resilient APIs, workflow orchestration, observability, and versioning with IT and platform teams.
• Extend shared enterprise Generative AI platforms, models, and agentic frameworks for biologics discovery.
• Connect experimental outputs to downstream property models and decisions across the design-make-test-learn cycle.
• Ensure workflow-generated data is high-quality, traceable, interoperable, and ready for AI-driven learning.

Requirements

• Master’s or Ph.D. in Computer Science, Engineering, or a related computational field, or a Bachelor’s degree with substantial relevant experience.
• At least 2 years of experience building scientific workflow orchestration or automation software, including agentic workflows.
• Hands-on experience designing real-time or near-real-time data pipelines and integrating heterogeneous scientific data and instrument outputs.
• Experience applying agentic AI and modern LLM-based agents, or comparable intelligent-automation systems, to scientific or laboratory workflows.
• Experience with shared or enterprise GenAI platforms and retrieval-augmented approaches such as RAG or GraphRAG.
• Strong communication skills and comfort working in ambiguity within a matrixed organization.

Nice to have

• Experience in biologics, drug discovery, high-throughput experimentation, or imaging.
• Exposure to lab automation, robotic systems, or cyber-physical R&D systems.
• Familiarity with MLOps, DevOps, workflow engines, and production monitoring or observability.
• Understanding of FAIR data, ontologies, semantic models, lineage, provenance, and AI-ready data standards.

Culture & Benefits

• Inclusive work environment centered on individual dignity, diversity, and equal opportunity.
• Medical, dental, vision, life insurance, disability, business accident, and group legal insurance programs may be available to eligible employees and dependents.
• Pension and 401(k) savings plans may be available to eligible employees.
• Vacation, sick time, holiday pay, floating holidays, and personal or family time are provided according to applicable employment terms.
• Cross-functional collaboration spans Discovery, Data Science, In Silico Discovery, Enterprise Generative AI, data infrastructure, and lab automation teams.