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Information Technology 🏢 Internship ⭐️ Verified

Summer Night Shift Internship - Paid

Global Tech Solutions
Portland, OR
Estimated Salary
USD 18 – USD 22
New
Live Update
16 Juli 2026
Deadline
16 Jul 2027

Job Description

Unlock your potential with a paid summer internship featuring a flexible night shift schedule! Global Tech Solutions offers an immersive opportunity for students to gain hands-on experience in a dynamic tech environment. This role combines competitive compensation with mentorship from industry leaders, allowing you to build skills while maintaining a balanced daytime schedule. Join our innovative team in Portland, Oregon, and accelerate your career trajectory.

As part of our commitment to professional growth, you'll receive structured training, exposure to cutting-edge projects, and networking opportunities. Our night shift format (10 PM - 6 AM) accommodates diverse schedules while providing dedicated focus time for deep work. This internship is also available in North Carolina, offering location flexibility for qualified candidates.

Responsibilities

  • Execute night shift operational tasks with precision and efficiency
  • Collaborate with cross-functional teams to deliver project milestones
  • Participate in agile development cycles and sprint planning
  • Document processes and maintain accurate technical records
  • Contribute to system monitoring and incident resolution
  • Support data analysis and reporting initiatives
  • Adhere to security protocols and compliance standards

Qualifications

  • Currently enrolled in a bachelor's program in Computer Science, Engineering, or related field
  • Availability to work 40 hours/week on night shift schedule (10 PM - 6 AM)
  • Proficiency in Python, Java, or JavaScript
  • Strong problem-solving and analytical thinking abilities
  • Experience with version control systems (Git)
  • Excellent written and verbal communication skills
  • Ability to work independently in a remote team environment

Required Skills

Python Java JavaScript Git Agile Data Analysis Problem Solving

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