Senior Agentic Workflow Engineer, Biologics Discovery
Johnson & Johnson
September 01, 2026
On-site
Titusville, NJ
IT
Senior Agentic Workflow Engineer (Agentic AI Workflows)
Location: Spring House, PA (strongly preferred), Titusville, NJ, Raritan, NJ, or Cambridge, MA (USA); or Madrid, Spain. No remote option.
Position Summary
Build and maintain agentic workflows and orchestration for scientific data analysis and secondary processing in biologics discovery. Implement automation/AI pipelines connecting automation software, data stores, models, and compute, partnering with senior engineers and teams across Discovery, Data Science, In Silico Discovery (ISD), Enterprise Generative AI, and data-infrastructure/lab automation to enable closed-loop feedback across the DMTL cycle.
Key Responsibilities
- Build and continuously improve agentic workflows to automate secondary analysis for biologics discovery assays.
- Develop real-time/near-real-time pipelines connecting automation, data stores, models, and compute.
- Implement resilient APIs, observability, versioning, and workflow orchestration end-to-end.
- Extend shared GenAI platforms/models/agentic frameworks for biologics discovery.
- Ensure semantically consistent, reusable, production-deployable outputs via ontology and MLOps collaboration.
Qualifications
Required:
- MS/PhD in CS/Engineering or related (or BS with substantial relevant experience).
- 2+ years building scientific workflow orchestration/automation software, including agentic workflows.
- Hands-on real-time/near-real-time data pipeline design integrating complex scientific/instrument outputs.
- Experience applying agentic AI/LLM agents to scientific/lab workflows.
- Experience with enterprise/shared GenAI platforms and retrieval-augmented approaches (RAG/GraphRAG).
- Strong communication in ambiguity.
Preferred:
- Drug discovery domain experience (biologics, high-throughput experimentation, imaging).
- Lab automation/robotics/cyber-physical R&D.
- MLOps/DevOps, workflow engines, production monitoring/observability.
- FAIR data, ontologies, semantic models, lineage/provenance, AI-ready data standards.
Compensation/Benefits (as stated)
- Base pay range: $109,000–$174,800; eligible for annual performance bonus.
- Medical/dental/vision, life insurance, short- and long-term disability, business accident insurance, group legal; 401(k) and pension plan eligibility.
- Time off: vacation up to 120 hours/yr, sick up to 40 hours/yr, holiday pay up to 13 days/yr; Work/Personal/Family time up to 40 hours/yr.
Location: Spring House, PA (strongly preferred), Titusville, NJ, Raritan, NJ, or Cambridge, MA (USA); or Madrid, Spain. No remote option.
Position Summary
Build and maintain agentic workflows and orchestration for scientific data analysis and secondary processing in biologics discovery. Implement automation/AI pipelines connecting automation software, data stores, models, and compute, partnering with senior engineers and teams across Discovery, Data Science, In Silico Discovery (ISD), Enterprise Generative AI, and data-infrastructure/lab automation to enable closed-loop feedback across the DMTL cycle.
Key Responsibilities
- Build and continuously improve agentic workflows to automate secondary analysis for biologics discovery assays.
- Develop real-time/near-real-time pipelines connecting automation, data stores, models, and compute.
- Implement resilient APIs, observability, versioning, and workflow orchestration end-to-end.
- Extend shared GenAI platforms/models/agentic frameworks for biologics discovery.
- Ensure semantically consistent, reusable, production-deployable outputs via ontology and MLOps collaboration.
Qualifications
Required:
- MS/PhD in CS/Engineering or related (or BS with substantial relevant experience).
- 2+ years building scientific workflow orchestration/automation software, including agentic workflows.
- Hands-on real-time/near-real-time data pipeline design integrating complex scientific/instrument outputs.
- Experience applying agentic AI/LLM agents to scientific/lab workflows.
- Experience with enterprise/shared GenAI platforms and retrieval-augmented approaches (RAG/GraphRAG).
- Strong communication in ambiguity.
Preferred:
- Drug discovery domain experience (biologics, high-throughput experimentation, imaging).
- Lab automation/robotics/cyber-physical R&D.
- MLOps/DevOps, workflow engines, production monitoring/observability.
- FAIR data, ontologies, semantic models, lineage/provenance, AI-ready data standards.
Compensation/Benefits (as stated)
- Base pay range: $109,000–$174,800; eligible for annual performance bonus.
- Medical/dental/vision, life insurance, short- and long-term disability, business accident insurance, group legal; 401(k) and pension plan eligibility.
- Time off: vacation up to 120 hours/yr, sick up to 40 hours/yr, holiday pay up to 13 days/yr; Work/Personal/Family time up to 40 hours/yr.