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Software Development Intern, AI-Assisted Development (Summer 2027) / Stagiaire en développement de  logiciel, développement assisté par l’IA (Été 2027)

Hewlett Packard Enterprise · St. Laurent, Quebec, Canada · hybrid

Software Development Intern, AI-Assisted Development (Summer 2027) / Stagiaire en développement de  logiciel, développement assisté par l’IA (Été 2027)

This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Description:

About the Role

We are looking for a motivated Software Engineering Intern to work closely with experienced senior developers on a next-generation network management service.

As an intern, you’ll contribute to a focused engineering project that may involve systems software, automated testing, performance and scale analysis, or developer tooling.

A key part of the internship will be learning how experienced engineers use AI throughout the software development lifecycle. You’ll use modern AI coding tools to understand existing code, investigate problems, implement changes, troubleshoot failures, generate and improve tests, and analyze results.

Just as importantly, you’ll learn how to question and validate AI-generated work using tests, measurements, code review, and engineering judgment.

What You’ll Work On

Depending on project priorities, your work could include:

- Improving parity and behavioral testing that compares expected behavior across implementations.

- Testing how network management pipeline components work together, from incoming data through processing to stored or displayed results.

- Developing end-to-end test scenarios for realistic user, network, or device workflows.

- Measuring performance and scale and comparing results across configurations or implementations.

- Improving the tools and automation engineers use to build, test, troubleshoot, and validate software changes.

- Using AI to understand unfamiliar areas of the codebase, investigate defects, analyze logs and test failures, and propose potential solutions.

- Participating in code reviews, debugging sessions, and technical discussions with experienced networking software engineers.

Working in an AI-Driven Engineering Process

This internship is about more than using AI to generate code.

You’ll learn how experienced developers integrate AI into their engineering workflow:

Senior developer defines the problem and constraints → Intern works with AI → AI assists with analysis and implementation → Tests and measurements validate the result → Intern reviews the output → Senior developer provides technical guidance

You’ll learn how to provide AI with the right technical context, recognize when its suggestions are incomplete or incorrect, and use objective evidence to determine whether a change actually works.

The goal is to develop both AI fluency and strong engineering judgment.

Mentorship

You’ll work closely with a senior developer who will help:

- Define and scope your project.

- Explain relevant system behavior and architecture.

- Help you navigate an existing codebase.

- Guide your use of AI development tools.

- Review your code, tests, and technical conclusions.

- Help you understand the engineering trade-offs behind different approaches.

You won’t be expected to make product or architecture decisions independently. Instead, you’ll get first-hand experience seeing how experienced engineers approach complex problems and how AI can augment that process.

What We’re Looking For

You may be a good fit if you:

- Are pursuing a degree in Computer Science, Software Engineering, Computer Engineering, or a related technical field.

- Have experience programming and debugging software.

- Understand basic software development concepts such as testing, version control, and code review.

- Have an interest in networking, systems software, or distributed systems.

- Are curious about Generative AI, LLMs, and AI-assisted software engineering.

- Enjoy investigating problems and understanding why something works or fails.

- Can communicate technical reasoning and findings clearly.

- Are comfortable questioning and verifying AI-generated suggestions rather than simply accepting them.

Experience with Rust, Linux, Git, networking, automated testing, containers, or AI coding tools is helpful, but not required.

What You’ll Learn

During the internship, you’ll gain hands-on experience with:

- AI-assisted software engineering.

- Working directly with senior software developers.

- Understanding and modifying a production-scale codebase.

- Network management and systems software.

- Automated and end-to-end testing.

- Performance and scale analysis.

- Debugging and root-cause investigation.

- Using tests and measurements to validate AI-generated software changes.

- Professional code review and engineering practices.

What Success Looks Like

A successful internship will deliver a useful, tested engineering improvement along with a clear explanation of:

- What problem was addressed.

- What changed.

- How AI was used.

- How the result was tested and validated.

- What was learned.

- What limitations or follow-up work remain.

The objective is not simply to generate more code with AI. It is to learn how to use AI effectively and responsibly within a disciplined software engineering process, while developing the technical judgment needed to produce software that engineers can understand, test, and trust.

Stagiaire en développement de  logiciel, développement assisté par l’IA (Été 2027)

À propos du poste

Nous recherchons un(e) stagiaire en génie logiciel motivé(e) qui travaillera en étroite collaboration avec des développeurs expérimentés sur un service de gestion de réseau de prochaine génération.

Dans le cadre de ce stage, vous contribuerez à un projet d’ingénierie ciblé pouvant toucher au logiciel système, aux tests automatisés, à l’analyse de la performance et de la mise à l’échelle, ou aux outils destinés aux développeurs.

Un aspect important du stage consistera à apprendre comment des développeurs expérimentés utilisent l’intelligence artificielle tout au long du cycle de développement logiciel. Vous utiliserez des outils modernes de développement assisté par l’IA pour comprendre du code existant, analyser des problèmes, apporter des modifications, diagnostiquer des défaillances, générer et améliorer des tests et analyser les résultats.

Tout aussi important, vous apprendrez à remettre en question et à valider le travail généré par l’IA au moyen de tests, de mesures, de revues de code et du jugement d’ingénierie.

Ce sur quoi vous travaillerez

Selon les priorités du projet, vous pourriez notamment :

- Améliorer des tests de parité et de comportement afin de comparer les résultats attendus entre différentes implémentations.

- Tester comment les composants d’une chaîne de traitement de gestion de réseau fonctionnent ensemble, depuis les données d’entrée jusqu’aux résultats stockés ou affichés.

- Développer des scénarios de test de bout en bout reproduisant des flux de travail réalistes impliquant des utilisateurs, des réseaux ou des équipements.

- Mesurer la performance et la capacité de mise à l’échelle, et comparer les résultats entre différentes configurations ou implémentations.

- Améliorer les outils et l’automatisation utilisés par les ingénieurs pour compiler, tester, diagnostiquer et valider les modifications logicielles.

- Utiliser l’IA pour comprendre des parties moins fa

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