IT Manager, Manufacturing Systems

Description

Tris Pharma, Inc. () is a leading privately-owned US biopharmaceutical company focused on development and commercialization of innovative medicines in ADHD, spectrum disorders, anxiety, pain and addiction addressing unmet patient needs. We have >150 US and International patents and market several branded ADHD products in the US. We also license our products in the US and ex-US markets. Our robust pipeline of innovative products employing our proprietary science and technology spans neuroscience and other therapeutic categories.

Our science and technology make us unique, but our team members set us apart; they’re the engine fueling Tris’ passion and innovation. Our colleagues understand the criticality of operating a successful business and take pride in the company’s success. Equally important is how we interact on a daily basis. We believe in each other and in respectful, open and honest communication to help support individual and team success.

We have a position available in our Monmouth Junction facility for an experienced IT Manager, Manufacturing Systems to support our on-site manufacturing operations.

This position is responsible for leading technology-enabled transformation across pharmaceutical manufacturing, packaging, quality, supply chain, engineering, warehouse and plant operations. The incumbent serves as a key IT partner to the manufacturing organization, with a primary focus on applying automation, data, analytics, AI and agentic AI capabilities to improve operational efficiency, compliance readiness, decision support and user productivity in a highly regulated manufacturing environment.

She/he helps shape and execute the company’s Artificial Intelligence (AI) transformation roadmap for manufacturing systems by identifying high-value use cases, coordinating business and technical requirements, enabling responsible AI tool adoption and helping to build scalable agentic AI solutions.

• Partners with Manufacturing, Packaging, Quality, Engineering, Supply Chain, Warehouse, Finance, and other business functions to identify opportunities where AI, automation, analytics, workflow and digital tools can reduce manual work, improve decision-making, strengthen compliance controls and increase operational effectiveness

• Leads discovery, prioritization, design and implementation of AI transformation use cases for manufacturing and related business functions, including agentic AI solutions, knowledge agents, workflow automation, digital assistants, exception monitoring and decision-support capabilities

• Assists in the building of an agentic AI platform by defining business use cases, data sources, system integrations, security controls, governance requirements, validation considerations, human-in-the-loop review points, support models and scalable implementation patterns

• Supports responsible AI adoption in a pharmaceutical manufacturing environment by ensuring solutions are aligned with applicable GxP expectations, data integrity principles, cybersecurity standards, privacy requirements, change control, testing, documentation and appropriate human oversight;
  Collaborates with IT infrastructure, cybersecurity, data and application teams to ensure manufacturing systems are secure, resilient, integrated, backed up, monitored and aligned with overall enterprise architecture and data governance standards

• Supports and improves technology used across manufacturing and plant operations (i.e., Enterprise Resource Planning (ERP) integrations, warehouse and inventory systems, barcode scanning, labeling, serialization, manufacturing execution, quality systems, equipment interfaces, data historians, reporting tools and other shop‑floor or plant applications, etc.)

• Builds strong relationships with manufacturing leaders and end users by providing responsive support, clear communication, effective training and practical guidance on system use, process impact and compliance expectations

• Leads or supports requirements gathering, process mapping, solution design, configuration, testing, user acceptance testing, validation documentation, implementation planning, training and post‑go‑live support for AI‑enabled…