IT Digital Ops & Supply Chain Data Co-Op
Listed on 2026-09-12
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IT/Tech
AI Engineer (Applied/Software), Data Engineering, Data Analyst, AI Business & Operations
Job Title:
IT Digital Ops & Supply Chain Data Co-op
Job Description:Here at Entegris, we use advanced science to enable technologies that transform the world, and we are seeking employees who have the drive to continue the mission.
The Role:Our site in Round Rock, TX is seeking an IT Digital Ops & Supply Chain Data Co-op to join our team for the Spring 2027 season. This assignment is intended to be 6 months in duration.
The IT Digital Ops & Supply Chain Data Co-op will join the Digital Operations & Supply Chain organization and work closely with data, analytics, AI, and business teams to support enterprise digital transformation initiatives. The position provides hands‑on experience developing and testing APS AI Agents, MCP-enabled Data Operations Agents, intelligent automation solutions, and Data-driven business capabilities that improve operational efficiency and decision-making across Supply Chain and Manufacturing functions.
The Co-Op will contribute to AI and Agentic AI projects involving data orchestration, enterprise integrations, analytics, and automation while gaining exposure to modern platforms, cloud technologies, and enterprise‑scale data management practices. The role will also support selected Master Data Management (MDM) initiatives to help ensure trusted, high‑quality data is available for AI, analytics, and business processes. This position offers a unique opportunity to work on emerging AI technologies and directly contribute to strategic initiatives that support Entegris' digital transformation roadmap.
- Develop and Support AI Agents:
Design, build, test, deploy, and enhance AI-powered business agents supporting Digital Operations and Supply Chain functions, including prompt engineering, workflow validation, proof-of-concepts, and business adoption activities. - Data Engineering, Integration & Automation:
Develop MCP-enabled data agents and support enterprise data access, orchestration, automation, integrations, data pipelines, profiling, transformation, enrichment, monitoring, and analytics workloads. - Analytics & Master Data Management:
Build dashboards, KPIs, and reporting capabilities to measure agent performance and business outcomes while supporting data quality, governance, reference data, and AI-driven master data use cases. - Testing, Documentation & Knowledge Management:
Validate AI agents, data pipelines, integrations, and automation workflows; maintain architecture diagrams, development artifacts, operational procedures, and training documentation. - Innovation & Continuous Improvement:
Research and evaluate emerging AI, agentic framework, MCP, and enterprise automation technologies to identify opportunities for business improvement and adoption.
Pursuing a Bachelor's or Master's degree in computer science, Information Systems, Data Analytics, Data Science, Artificial Intelligence, Software Engineering, Supply Chain Analytics, or a related technical field.
Previous internship, co-op, academic project, or hands‑on experience in one or more of the following areas is preferred:
Artificial Intelligence (AI) or Machine Learning, Data Engineering or Data Analytics, Software Development Cloud Technologies, Enterprise Data Management, Automation and Workflow Development, Experience with AI projects, agents, LLMs, MCP frameworks, data pipelines, or analytics platforms is highly desirable.
Preferred certifications or coursework:
Microsoft AI Fundamentals (AI-900), Microsoft Azure Fundamentals (AZ-900), Google Cloud Digital Leader or Generative AI coursework, Data Analytics, Python, Machine Learning, or Cloud Computing certifications, Academic coursework related to AI, Data Engineering, or Software Development.
Computer…
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