IT Manager, Manufacturing Systems

Tris Pharma•Monmouth Junction, NJ

5d•Hybrid

About The Position

Tris Pharma, Inc. is seeking an experienced IT Manager, Manufacturing Systems to support its on-site manufacturing operations in Monmouth Junction. This role is responsible for leading technology-enabled transformation across pharmaceutical manufacturing, packaging, quality, supply chain, engineering, warehouse, and plant operations. The IT Manager will act as a key IT partner to the manufacturing organization, focusing on applying automation, data, analytics, AI, and agentic AI capabilities to enhance operational efficiency, compliance readiness, decision support, and user productivity within a highly regulated environment. This includes shaping and executing the company’s AI transformation roadmap for manufacturing systems by identifying high-value use cases, defining requirements, enabling responsible AI tool adoption, and building scalable agentic AI solutions. The role involves close collaboration with various business functions to identify opportunities for AI, automation, and digital tools to reduce manual work, improve decision-making, strengthen compliance, and increase operational effectiveness. The IT Manager will lead the discovery, prioritization, design, and implementation of AI transformation use cases, including agentic AI solutions, knowledge agents, workflow automation, digital assistants, and decision-support capabilities. They will also support the building of an agentic AI platform by defining use cases, data sources, integrations, security, governance, validation, and support models. A key aspect of the role is ensuring responsible AI adoption in a pharmaceutical manufacturing setting, adhering to GxP expectations, data integrity principles, cybersecurity standards, privacy requirements, and change control processes. The IT Manager will collaborate with IT infrastructure, cybersecurity, data, and application teams to ensure manufacturing systems are secure, resilient, integrated, and aligned with enterprise architecture. They will support and improve technology across manufacturing and plant operations, including ERP integrations, warehouse systems, barcode scanning, serialization, manufacturing execution systems, quality systems, and shop-floor applications. Building strong relationships with manufacturing leaders and end-users through responsive support, clear communication, and effective training is crucial. The role also involves leading or supporting requirements gathering, process mapping, solution design, testing, validation documentation, implementation planning, training, and post-go-live support for AI-enabled and manufacturing system enhancements, establishing adoption practices for AI-enabled tools.

Requirements

Bachelors degree in IT, Computer Science, Engineering, Data Science or related technical field and minimum 7 years progressive IT experience supporting manufacturing systems, digital transformation, automation, analytics, AI-enabled solutions, ERP and/or plant technology in a pharmaceutical, biotechnology, medical device or related regulated manufacturing environment OR a combination of education and experience supporting manufacturing systems, digital transformation, automation, analytics, AI-enabled solutions, ERP and/or plant technology in the above industries
Strong practical understanding and working knowledge/ability to use Microsoft AI and analytics stack (i.e., Microsoft 365 Copilot, Copilot Studio, Power Platform, Power Automate, Power Apps, Power BI, Fabric, Azure AI services, Azure OpenAI, Microsoft Graph, Dataverse, SharePoint, etc.)
Strong understanding of pharmaceutical manufacturing operations including current Good Manufacturing Practices (cGMP) expectations, computer system validation, data integrity, audit readiness, change control, testing and controlled documentation practices
Understanding of Microsoft security, governance, and compliance capabilities relevant to AI adoption, including Microsoft Entra ID, Purview, sensitivity labels, data loss prevention, access controls, etc.
Ability to design and support Copilot Studio agents, Power Automate workflows, knowledge-based assistants, retrieval-augmented generation solutions, and human-in-the-loop AI processes that are secure, supportable, auditable, and aligned with business and compliance expectations.
Working knowledge and/or experience with ERP systems

Responsibilities

Leading technology-enabled transformation across pharmaceutical manufacturing, packaging, quality, supply chain, engineering, warehouse and plant operations.
Applying automation, data, analytics, AI and agentic AI capabilities to improve operational efficiency, compliance readiness, decision support and user productivity.
Shaping and executing the company’s Artificial Intelligence (AI) transformation roadmap for manufacturing systems.
Identifying high-value use cases, coordinating business and technical requirements, enabling responsible AI tool adoption and helping to build scalable agentic AI solutions.
Partnering 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.
Leading 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.
Assisting 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.
Supporting 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.
Collaborating 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.
Supporting and improving 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.).
Building 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.
Leading or supporting requirements gathering, process mapping, solution design, configuration, testing, user acceptance testing, validation documentation, implementation planning, training and post-go-live support for AI-enabled and manufacturing system enhancements.
Establishing adoption practices for AI-enabled tools, including user training, prompt and agent usage guidance, knowledge management, feedback loops, performance measures and continuous improvement of deployed solutions.