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Intern/Software Engineering

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Calibre Systems

Alexandria, VA (In Person)

Full-Time

Posted 3 days ago (Updated 11 hours ago) • Actively hiring

Expires 6/9/2026

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Job Description

CALIBRE is an employee-owned, mission-focused solutions and digital transformation company. We are seeking a Software Engineering Summer Intern to support the CALIBRE Innovation Center in the design, development, integration, and testing of emerging software solutions. This intern will work with a cross-functional team of software engineers, data scientists, and analysts supporting rapid prototyping and application development efforts, including AI-enabled solutions, service integrations, and cloud-based platforms. This role is ideal for a candidate with a strong interest in Python-based software development , AI/ML libraries , application integration , and cloud technologies , especially AWS . The intern will contribute to fast-moving projects involving prototype development, feature implementation, code reviews, testing, and technical documentation. This position is expected to be onsite or hybrid located in Alexandria, Virginia What You'll Do As a Software Engineering Summer Intern, you may support activities such as: Assist in designing, building, and testing software applications and prototypes using Python Support development of AI-enabled tools and workflows using modern AI/ML libraries and frameworks Help integrate external and internal services through APIs , web services, and other application interfaces Contribute to rapid prototyping efforts for new product concepts, internal tools, and proof-of-concept solutions Participate in Agile team activities, including sprint planning, standups, backlog refinement, and technical reviews Collaborate with software engineers, analysts, and data scientists on feature development and solution design Perform unit testing, functional testing, debugging, and defect resolution Participate in code reviews and incorporate feedback into iterative improvements Help create and maintain technical documentation, developer notes, and user-facing documentation Support deployment and development activities in cloud environments, including AWS Contribute to software quality, maintainability, and secure development practices Required Skills Currently pursuing a Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems , or a related technical field Familiarity with software development fundamentals, including object-oriented programming, version control, and debugging Experience developing in Python Familiarity with AI/ML development concepts and common libraries or frameworks Exposure to service integration , including REST APIs, web services, or system-to-system interfaces Familiarity with one or more cloud platforms, preferably AWS Interest in rapid prototyping , application development, and turning ideas into working software Interest in code reviews , testing , and documentation Strong problem-solving, communication, and teamwork skills Ability to work effectively in a collaborative, fast-paced environment Preferred Qualifications Experience with AI libraries, frameworks, or tooling used in application development Exposure to cloud-native development or deployment practices in AWS Familiarity with Git-based development workflows and CI/CD concepts Experience with scripting, automation, or lightweight full-stack application development Familiarity with secure software development, DevSecOps, or software quality practices Prior coursework or project experience involving: prototyping AI-enabled applications integrating multiple services or data sources testing and documenting software solutions Agentic Coding development experience is a plus required Experience The ideal candidate is curious, hands-on, and excited to build. They enjoy experimenting with new technologies, learning quickly, and contributing to practical software solutions.
They are especially interested in:
building and refining working prototypes developing Python applications integrating services and APIs applying AI libraries to real use cases improving code quality through testing and review documenting work clearly for teammates and stakeholders

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