Enterprise AI Engineer: GenAI & Scalable Production ML

A growing advanced manufacturing organization is seeking an experienced AI Engineer to help lead enterprise AI adoption initiatives within a highly regulated environment. This role focuses on designing, developing, and deploying scalable AI and machine learning solutions that improve operational efficiency, business processes, and data-driven decision making.

This position offers the opportunity to influence AI strategy, architect enterprise-grade AI systems, and collaborate cross-functionally with engineering, operations, and technology teams.

• Drive AI strategy and support enterprise AI adoption initiatives.
• Design secure, scalable, and responsible AI architectures within regulated environments.
• Integrate AI solutions with existing enterprise systems and infrastructure.
• Develop end-to-end AI and machine learning solutions from proof of concept through production deployment.
• Architect data pipelines and workflows for structured, semi-structured, and unstructured data sources.
• Collaborate with stakeholders across engineering, operations, and support functions to identify high-value AI use cases.
• Design and deploy GenAI-enabled applications and intelligent automation solutions.
• Ensure alignment with enterprise data governance, retention, and compliance standards.
• Apply analytical and data science methodologies to solve business problems and improve operational efficiency.
• Utilize lean and continuous improvement principles to optimize processes.

• Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or related field.
• 5+ years of experience deploying AI/ML solutions at scale.

• Experience with Generative AI, AI agents, and/or reinforcement learning.
• Experience with major machine learning frameworks and AI platforms.
• Experience developing and deploying machine learning solutions into production environments.
• Familiarity with NLP and document AI technologies.
• Strong understanding of data modeling, data architecture, metadata management, and data integration patterns.
• Experience handling unstructured data including text, images, and video.
• Strong analytical and problem-solving abilities.

• Experience in regulated manufacturing, aerospace, defense, or industrial environments.
• Familiarity with MES, ERP, quality systems, or manufacturing data ecosystems.