Intern - Cloud Engineer

GM Financial•Irving, TX

3d•Hybrid

About The Position

The Cloud Engineer Intern works collaboratively in an agile team to implement highly available and secure cloud technologies. The intern monitors and optimizes cloud implementations for efficiency and supports and collaborates with other teams and projects, particularly DevOps, platform, and automation teams. The role includes building secure cloud solutions using public cloud platforms such as Microsoft Azure and Amazon Web Services; working with product owners and managers to establish application service-level objectives and consequences for missing them; and collaborating with development teams to troubleshoot and resolve problems in cloud-hosted environments. The 11-week internship runs from May 26 through August 6, 2027, and includes executive and peer networking, independent and team project experiences, philanthropic activities, career development, and the opportunity to apply for full-time career positions. The work environment is described as flexible and hybrid, with three days a week in the office, Tuesday through Thursday. Compensation is described as competitive pay.

Requirements

Be a current student pursuing a bachelor's degree or higher from an accredited college or university in Finance, Accounting, Economics, or another related major.
Have at least one semester remaining upon the start of the internship.
Have a minimum overall GPA of 3.0 on a 4-point scale.
Have strong written and verbal communication skills.
Have strong analytical, quantitative, problem-solving, and conceptual skills.
Be detail-oriented and able to prioritize tasks to meet deadlines.
Be able to work independently or in a team setting.
Have excellent oral and written communication, organizational, and time-management skills.

Nice To Haves

Junior or Senior classification is preferred.
Previous internships are a plus.
Ability to use AI tools, such as Microsoft Copilot, to support daily work.
Skills in evaluating AI outputs for accuracy, compliance, and bias.
Experience integrating AI into workflows to improve efficiency or insights.
Familiarity with AI-assisted research, summarization, and content generation.
Understanding of responsible AI use, including ethics and data protection.
Experience with AI-assisted software development or automation.
Knowledge of prompting techniques to improve output quality.
Awareness of emerging generative AI capabilities and limitations.

Responsibilities

Build secure cloud solutions in public cloud platforms such as Microsoft Azure and Amazon Web Services.
Collaborate with product owners and managers to establish service-level objectives for applications and agreed consequences when objectives are not met.
Collaborate with development team members to troubleshoot and resolve problems in cloud-hosted environments.
Monitor and optimize cloud implementations for efficiency.
Support and collaborate with DevOps, platform, and automation teams and projects.
Work collaboratively in an agile team.
Manage multiple projects and tasks simultaneously.
Give presentations and communicate with business leaders.