Process Engineer: Models, MES & Automation

ATI; Brackenridge (PA); On-site; USD 75,000 - 110,000; Full time

Job summary

ATI is seeking a Process Engineer for the Brackenridge Operations HRPF in Brackenridge, PA. This role requires shift rotation and weekend on-call availability, acting as the primary operational resource for PC&A systems.

You will monitor process performance, product quality, and mill health while coordinating with Operations, Quality, and Maintenance to implement approved adjustments within authority. Responsibilities include monitoring Level 1/2 models, MES, and data to identify abnormal

Qualifications

• Bachelor of Science degree in Mechanical Engineering, Electrical Engineering, Manufacturing Engineering, Metallurgical Engineering, or related field.
• Experience with process control & automation systems is a plus.
• Strong analytical, troubleshooting, and problem-solving skills required.

Responsibilities

• Develop and maintain knowledge of Level 1/2 processes, MES, and automation systems.
• Monitor process models and data to maintain stability, quality, and mill health.
• Implement mill setup adjustments within operating limits to maintain stability and quality.
• Review production schedules to identify risks and mitigation strategies.
• Provide technical investigations and continuous improvement support to Process Models and Quality teams.

Skills

Industrial automation

Manufacturing data analysis

Root cause investigations

Communication

Problem solving

Education

Bachelor of Science in Mechanical Engineering

Tools

MES

Microsoft Office

Job description

ATI is seeking a Process Engineer for the Brackenridge Operations HRPF in Brackenridge, PA. This role requires shift rotation and weekend on-call availability, acting as the primary operational resource for PC&A systems.

You will monitor process performance, product quality, and mill health while coordinating with Operations, Quality, and Maintenance to implement approved adjustments within authority. Responsibilities include monitoring Level 1/2 models, MES, and data to identify abnormal