AI-Driven Systems Design & QA Intern (Summer 2027)

McKesson; United States; On-site; USD 24,000 - 40,000; Full time

Benefits offered by this job

Paid Internship

Networking with executives

Structured coaching

Hands-on training

Job summary

McKesson is seeking an intern to support MAPS System Design Engineering and Quality teams in simulation modeling, design validation, portfolio analysis, and AI-enabled process improvements. This paid internship runs full-time for 10 weeks at our Irving, TX location and includes networking and executive exposure.

Preferred candidates are pursuing Industrial/Systems Engineering, Engineering Management, Data Analytics, or related fields with an analytical mindset and interest in automation and AI.

Qualifications

• Pursuing a degree in Industrial Engineering, Systems Engineering, Engineering Management, Data Analytics, or a related field.
• Analytical mindset with strong problem-solving skills.
• Experience with data analysis tools, modeling, or simulation software preferred.

Responsibilities

• Assist with Simio modeling and simulation activities.
• Support analysis of automation system performance and design alternatives.
• Participate in requirements validation, testing, and quality assurance activities.
• Analyze operational and performance data to identify trends and improvement opportunities.
• Evaluate opportunities to apply AI and automation to engineering and quality processes.
• Create dashboards, documentation, and presentations to support decision making.

Skills

Analytical mindset

Problem-solving skills

Interest in automation and AI

Education

Industrial/Systems Engineering or related field

Tools

Data analysis tools

Modeling software

Simulation software

Job description

McKesson is seeking an intern to support MAPS System Design Engineering and Quality teams in simulation modeling, design validation, portfolio analysis, and AI-enabled process improvements. This paid internship runs full-time for 10 weeks at our Irving, TX location and includes networking and executive exposure.

Preferred candidates are pursuing Industrial/Systems Engineering, Engineering Management, Data Analytics, or related fields with an analytical mindset and interest in automation and AI.