Principal Data Scientist - DDSAI - Agentic Lab Automation
Johnson & Johnson
June 30, 2026
Remote friendly (Spring House, PA)
United States
IT
About The Role
Principal Scientist, Agentic Lab Automation (Spring House, PA). Help build a next-generation DMTA discovery engine integrating robotic lab execution, real-time data pipelines, intelligent orchestration, and agentic AI workflows.
Key Responsibilities
- Translate scientific priorities into automation and AI roadmaps.
- Design, configure, integrate, and improve AI execution for robotic lab systems supporting high-throughput data generation.
- Build/oversee real-time pipelines connecting automation software, data stores, models, and compute.
- Partner with IT/platform teams on resilient APIs, observability, versioning, and workflow orchestration.
- Design laboratory workflows optimized for AI-driven learning (not just throughput).
- Enable closed-loop feedback across the DMTA process so outputs improve downstream models/decisions.
- Apply agentic AI to compress cycle time, reduce manual intervention, and improve reproducibility.
- Ensure data is high-quality, traceable, interoperable, and AI-ready (metadata/provenance/lineage/governance).
- Standardize assay outputs; semantically enrich datasets; support discoverability.
- Provide cross-functional technical leadership across Discovery, Data Science, and IT.
- Evaluate vendors/tools for robotics, AI orchestration, and AI-enabled lab execution.
Qualifications
Required: Ph.D. (or equivalent) in Engineering/Automation/Robotics/CS/Biomedical/Chemical/Systems/Computational Biology or related; significant industry experience in lab automation/AI-enabled experimentation/autonomous workflows; expertise in robotic lab systems/workflow orchestration/lab informatics/platform integration/automation/cyber-physical systems; experience with real-time/near-real-time data pipelines and heterogeneous instrument data integration; ability to partner with scientists; strong communication and stakeholder management.
Preferred: Agentic AI/AI-ML/optimization/intelligent decision systems in scientific workflows; MLOps/DevOps, workflow engines, production monitoring/observability; FAIR/ontologies/semantic models/lineage/provenance/AI-ready standards; drug discovery domain experience (e.g., small molecules, biologics, peptides, HT experiments, imaging, human-relevant models).
Benefits (time off, subject to policy/date of hire)
Vacation 120 hrs/yr; Sick time 40 hrs/yr (state-dependent); Holiday pay incl. floating holidays 13 days/yr; Work/Personal/Family time up to 40 hrs/yr; Parental leave 480 hrs; Bereavement leave 240 hrs (immediate) / 40 hrs (extended); Caregiver leave 80 hrs; Volunteer leave 32 hrs; Military spouse time-off 80 hrs/yr.
Principal Scientist, Agentic Lab Automation (Spring House, PA). Help build a next-generation DMTA discovery engine integrating robotic lab execution, real-time data pipelines, intelligent orchestration, and agentic AI workflows.
Key Responsibilities
- Translate scientific priorities into automation and AI roadmaps.
- Design, configure, integrate, and improve AI execution for robotic lab systems supporting high-throughput data generation.
- Build/oversee real-time pipelines connecting automation software, data stores, models, and compute.
- Partner with IT/platform teams on resilient APIs, observability, versioning, and workflow orchestration.
- Design laboratory workflows optimized for AI-driven learning (not just throughput).
- Enable closed-loop feedback across the DMTA process so outputs improve downstream models/decisions.
- Apply agentic AI to compress cycle time, reduce manual intervention, and improve reproducibility.
- Ensure data is high-quality, traceable, interoperable, and AI-ready (metadata/provenance/lineage/governance).
- Standardize assay outputs; semantically enrich datasets; support discoverability.
- Provide cross-functional technical leadership across Discovery, Data Science, and IT.
- Evaluate vendors/tools for robotics, AI orchestration, and AI-enabled lab execution.
Qualifications
Required: Ph.D. (or equivalent) in Engineering/Automation/Robotics/CS/Biomedical/Chemical/Systems/Computational Biology or related; significant industry experience in lab automation/AI-enabled experimentation/autonomous workflows; expertise in robotic lab systems/workflow orchestration/lab informatics/platform integration/automation/cyber-physical systems; experience with real-time/near-real-time data pipelines and heterogeneous instrument data integration; ability to partner with scientists; strong communication and stakeholder management.
Preferred: Agentic AI/AI-ML/optimization/intelligent decision systems in scientific workflows; MLOps/DevOps, workflow engines, production monitoring/observability; FAIR/ontologies/semantic models/lineage/provenance/AI-ready standards; drug discovery domain experience (e.g., small molecules, biologics, peptides, HT experiments, imaging, human-relevant models).
Benefits (time off, subject to policy/date of hire)
Vacation 120 hrs/yr; Sick time 40 hrs/yr (state-dependent); Holiday pay incl. floating holidays 13 days/yr; Work/Personal/Family time up to 40 hrs/yr; Parental leave 480 hrs; Bereavement leave 240 hrs (immediate) / 40 hrs (extended); Caregiver leave 80 hrs; Volunteer leave 32 hrs; Military spouse time-off 80 hrs/yr.