Director, R&D DDSAI Therapeutics Development Supply, AI Solutions

Johnson & Johnson

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Spring House, PAMalvern, PA
Salary
$164,000–$282,900 / yr
Posted
6 days ago
Freshness
Confirmed live yesterday
Closes
Oct 16, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $246k
This role $223k
$148k most similar roles pay here $313k

This role pays less than 67% of similar roles. Most pay $209,984–$282,500 — the shaded band above. At the midpoint, this role pays about $223k versus about $246k for comparable roles.

Based on 240 similar postings.

Employer

About Johnson & Johnson

Johnson & Johnson is a multinational corporation operating in three main segments: consumer health products, pharmaceuticals, and medical devices, known for brands like Tylenol, Band-Aid, and Janssen. Industry: Pharmaceuticals & Medical Devices

Johnson & Johnson currently has 61 open roles on FindRole.

Listed pay typically runs $109,000–$177,100 across 57 roles with salary data.

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View all roles at Johnson & Johnson

At a glance

TL;DR · Director, R&D DDSAI Therapeutics Development Supply, AI Solutions

Director, R&D DDSAI Therapeutics Development Supply - AI Solutions leads a team of applied data scientists, machine learning scientists, and GenAI/agentic engineers within the R&D Data, Data Science and AI organization. This role focuses on transforming scientific and operational data into AI-driven workflows to support Thermodynamics Development & Supply across chemistry, manufacturing, and clinical supply chains. The successful candidate will design, build, and deliver solutions including model-informed process designs, lab-in-the-loop workflows, and scientific reasoning agents. Key responsibilities include defining the AI strategy, ensuring GxP compliance, and managing the lifecycle of production-level products. Required technical expertise includes Python, statistical modeling, GenAI/LLMs, agentic patterns, and cloud environments like AWS and Snowflake. The role addresses complex pharmaceutical R&D challenges by creating reusable capabilities to accelerate the delivery of next-generation therapies in regulated manufacturing and laboratory environments.

What you'll do

  • Define and execute the TDS AI Solutions strategy and portfolio roadmap aligned with organizational priorities.
  • Lead the design, build, validation, and delivery of AI/ML, generative AI, and agentic co-scientist solutions.
  • Establish reusable solution patterns, shared components, and evaluation frameworks to scale across various functions.
  • Serve as the technical owner for shared AI capabilities by representing requirements to cross-functional platform and technology teams.
  • Enforce standards for model development, including version control, testing, documentation, and compliance in regulated environments.
  • Manage the full lifecycle of models, including monitoring, retraining, and determining criteria for scaling or retiring solutions.
  • Recruit, develop, and lead a team of data scientists, machine learning scientists, and GenAI engineers.
  • Collaborate with process chemists and supply chain experts to translate complex scientific problems into actionable technical workflows.

What we're looking for

  • Advanced degree in Engineering, Data Science, Computer Science, Statistics, Operations Research, or a related quantitative field.
  • 10+ years of experience in applied data science, machine learning, or AI solution development.
  • At least 3 years of experience in a people leadership role.
  • Hands-on expertise in Python, applied ML and statistical modeling, GenAI/LLMs, agentic patterns, and cloud environments like AWS and Snowflake.
  • Proven track record of building teams that deliver AI/ML into production with sustained adoption and reusable components.
  • Ability to influence and align technical and business stakeholders at the Senior Director and VP levels.
  • Experience in pharmaceutical R&D, CMC/process development, life sciences manufacturing, clinical supply, or GxP environments (preferred).
  • Experience delivering generative AI and agentic solutions, MLOps practices, knowledge graphs, and semantic layers (preferred).

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