Principal Agentic Workflow & AI Engineer, Biologics Discovery

About the role

Johnson & Johnson Innovative Medicine is seeking a senior expert to design and build the agentic layer of its Biologics Discovery data engine. The role focuses on automating secondary data processing, orchestrating analyses, and linking experimental outputs to models across the design‑make‑test‑learn cycle.

Key responsibilities

• Design, configure, and continuously improve agentic workflows that automate secondary analysis for biologics discovery assays.
• Build and oversee real‑time pipelines connecting automation software, data stores, models, and compute environments.
• Partner with IT, platform, Enterprise Generative AI, ontology, and MLOps teams to implement resilient APIs, observability, versioning, and workflow orchestration.
• Develop AI‑driven learning workflows that enable closed‑loop feedback across the DMTL cycle and ensure high‑quality, AI‑ready data with strong metadata and provenance.
• Set technical direction, evaluate emerging agentic AI methods, and mentor engineers and data scientists.

Required profile

• Advanced degree (Ph.D. preferred) in Computer Science, Engineering, or a related computational field.
• At least 3 years of experience building scientific workflow orchestration and automation software, including agentic AI.
• Hands‑on experience with real‑time data pipelines and integration of heterogeneous scientific data.
• Strong communication and stakeholder‑management skills in matrixed organizations.

Required skills

• Agentic AI and LLM‑based agents applied to scientific or laboratory workflows.
• Design and implementation of real‑time or near‑real‑time data pipelines.
• Experience with enterprise or shared Generative AI platforms and retrieval‑augmented approaches (RAG, GraphRAG).
• API development, observability, versioning, and workflow orchestration tools.
• MLOps/DevOps practices, workflow engines, and production‑grade monitoring.