Digital Automation Manager Jobs (NOW HIRING)

Overview

Position Summary

The Manufacturing AI & Automation Engineer is responsible for identifying, developing, and implementing artificial intelligence, digital automation, and intelligent manufacturing solutions across production and engineering operations.

This role will focus on using AI to eliminate manual and clerical work, improve access to manufacturing knowledge, accelerate process documentation, enable paperless factory initiatives, optimize manufacturing processes, and develop intelligent automation solutions for production operations.

The Manufacturing AI & Automation Engineer will design, build, and deploy intelligent applications using large language models, pre-trained foundation models, automation platforms, data pipelines, and manufacturing systems to automate workflows and solve complex operational problems.

Applications may include AI-assisted process documentation, intelligent document search and retrieval, automated engineering workflows, manufacturing knowledge management, process optimization, machining applications, automated inspection, production analytics, and factory automation.

The ideal candidate combines an understanding of manufacturing and engineering processes with practical experience applying AI and digital automation technologies to real-world problems.

Key Responsibilities

• Identify and lead opportunities to apply artificial intelligence, digital automation, and intelligent systems across manufacturing and engineering operations.
• Develop AI-enabled tools to automate repetitive engineering, manufacturing, quality, and clerical documentation activities.
• Develop solutions that support the transition toward a paperless factory, including digital workflows, electronic records, intelligent documentation, and automated information retrieval.
• Use AI to create, improve, standardize, and maintain work instructions, manufacturing procedures, process documentation, standard work, and other technical content.
• Develop intelligent search and knowledge-management systems that allow employees to quickly locate and retrieve relevant procedures, specifications, drawings, engineering documents, historical information, and manufacturing knowledge.
• Apply large language models and foundation models to manufacturing workflows using tools such as Claude and other enterprise AI platforms.
• Develop AI-assisted workflows that connect manufacturing information across systems and reduce manual data entry, document creation, transcription, searching, and administrative work.
• Identify opportunities to integrate AI with manufacturing equipment, automation systems, inspection processes, machining operations, and production data.
• Evaluate and implement AI applications for machine optimization, process parameter optimization, predictive analytics, anomaly detection, automated inspection, computer vision, and quality control.
• Identify opportunities for robotic, software, and digital process automation throughout manufacturing operations.
• Develop applications, scripts, integrations, or automated workflows connecting AI tools with manufacturing and business systems.
• Evaluate existing manufacturing processes and determine where AI or automation can improve cycle time, productivity, quality, cost, capacity, decision-making, and employee efficiency.
• Work with manufacturing, quality, operations, IT, and engineering teams to translate business and production problems into practical AI solutions.
• Develop proof-of-concept solutions and transition successful concepts into reliable production tools.
• Establish methods to validate AI-generated information and ensure appropriate accuracy, traceability, security, and human oversight.
• Develop standards and best practices for responsible use of AI within manufacturing and engineering operations.
• Train engineers, technicians, manufacturing personnel, and other users on newly implemented AI and automation tools.
• Track the effectiveness of implemented solutions and quantify improvements in productivity, quality, cost, and process efficiency.

Required Qualifications

• Bachelor’s degree in Manufacturing Engineering, Mechanical Engineering, Industrial Engineering, Systems Engineering, Computer Engineering, Computer Science, or a related technical discipline. 
• 5–10 years of engineering experience in Manufacturing Engineering, Mechanical Engineering, Industrial Engineering, Systems Engineering, Computer Engineering, Computer Science, or a related technical field, with a strong focus on automation and digital technologies and demonstrated experience applying AI and data-driven solutions to manufacturing, engineering, or operational environments.
• Experience applying artificial intelligence, large language models (LLMs), digital automation, or intelligent workflow technologies to practical engineering or business challenges. 
• Strong understanding of manufacturing, engineering, operations, and industrial processes, with the ability to identify opportunities for process improvement and automation. 
• Experience evaluating manual or inefficient workflows and developing scalable automated or digital solutions. 
• Ability to translate manufacturing and operational requirements into effective technical solutions and bridge communication between engineering, manufacturing, operations, quality, and IT teams. 
• Experience working with structured and unstructured data, technical documentation, and enterprise information systems. 
• Strong analytical and structured problem-solving skills, with the ability to evaluate emerging technologies and identify practical, high-value applications. 
• Demonstrated ability to independently lead technical projects from opportunity identification and concept development through prototyping, implementation, validation, and adoption. 
• Understanding of data quality, information security, traceability, validation, and human oversight when implementing AI and automation solutions. 
• Ability to evaluate and quantify the operational and business impact of AI, automation, and process-improvement initiatives. 
• Strong written and verbal communication skills with the ability to communicate technical concepts effectively across technical and non-technical teams. 

Preferred Qualifications

• Experience using Claude or other enterprise AI platforms in professional or manufacturing applications. 
• Experience developing solutions using LLMs, foundation models, retrieval-augmented generation (RAG), AI agents, APIs, or enterprise AI platforms. 
• Proficiency with Python, SQL, APIs, scripting, or low-code/no-code automation platforms. 
• Experience integrating AI or automation solutions with MES, ERP, QMS, PLM, document management, or other manufacturing systems. 
• Experience leading manufacturing workflow automation, digital transformation, paperless manufacturing, or digital work-instruction initiatives. 
• Experience applying AI, machine learning, data analytics, or computer vision to manufacturing processes, inspection, equipment performance, or process optimization. 
• Experience with machining, CNC processes, robotics, industrial automation, machine connectivity, or smart manufacturing technologies. 
• Familiarity with Lean manufacturing, Six Sigma, continuous improvement, or process optimization methodologies. 
• Experience deploying AI solutions within enterprise environments involving sensitive, proprietary, or controlled technical information.