Director R&D AI Systems

At Johnson & Johnson,we believe health is everything.

Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions are personal.Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.Learn more at jnj.com

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world.

We provide an inclusive work environment where each person is considered as an individual.

At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:
Technology Product & Platform Management

Job Sub Function:
Intelligent Automation Engineering

Job Category:
People Leader

All Job Posting Locations:
Raritan, New Jersey, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description:

We are searching for the best talent for Director, R&D AI Systems to be located in Titusville, NJ, Spring House, PA or Raritan, NJ.

The Director, R&D AI Systems is responsible for leading the technology capabilities that operationalize AI, GenAI, LLM, agentic, knowledge graph, and model lifecycle platforms across Innovative Medicine R&D.

The role ensures that AI products move from experimentation to reliable, secure, governed, scalable, observable, and cost-effective production services.

This leader partners across DDSAI (R&D DATA SCIENCE TEAM), Technology Services, Information Security & Risk Management, Enterprise Architecture, data product teams, model builders, product owners, and business stakeholders to run an integrated Data & AI operating model.

The role translates AI use cases, model evaluation needs, and business priorities into production-grade platforms, engineering practices, deployment patterns, and operational controls.

The role is accountable for MLOps and LLMOps management, model and agent deployment, agentic platform operations, knowledge graph enablement, AI engineering best practices, AI scorecards, token cost management, security red-teaming, third-party model licensing and SLAs, enterprise GenAI governance, and approved agentic development patterns.

Key Responsibilities

MLOps and LLMOps Platform Management


* Lead strategy, operations, and adoption for Cross R&D MLOps and LLMOps platforms, and approved enterprise model lifecycle tooling.


* Establish repeatable workflows for model registration, packaging, testing, deployment, monitoring, rollback, lifecycle management, and model retirement.


* Partner with DDSAI model builders and researchers to harden models for regulated, scalable, production-grade deployment.


* Ensure MLOps and LLMOps platforms meet security, privacy...