Software Engineer Intern

NetApp, Inc.

About The Position

NetApp builds intelligent data infrastructure that helps customers manage, protect, and extract value from their data—anywhere it lives. Our engineering teams design and deliver highly scalable, reliable, and secure software that powers mission-critical workloads across the globe. As a Software Engineer Intern, you will work alongside experienced engineers to design, build, test, and deploy production-quality software systems. You will contribute to real-world products used by thousands of customers, gaining hands-on experience with modern software engineering practices, distributed systems, cloud-scale technologies and Generative AI–enabled development workflows. You will also gain exposure to Generative AI technologies, agentic frameworks, and AI copilots, learning how intelligent agents and developer assistance tools can accelerate software development, improve code quality, and enable new product capabilities. At NetApp, we believe interns are not observers, they are builders. You will have the opportunity to make meaningful contributions while learning how high-impact software is designed, implemented, and operated at scale.

Requirements

Strong foundation in computer science fundamentals including data structures, algorithms, and object-oriented design.
Hands-on programming experience in one or more languages such as Python, JavaScript or NodeJS
Familiarity with software development lifecycle concepts, including version control (e.g., Git), testing, and debugging.
Basic understanding of operating systems, networking, or distributed systems concepts.
Awareness of Generative AI concepts, including large language models (LLMs), prompt engineering, or AI-assisted development tools.
Ability to learn new technologies quickly and apply them effectively.
Clear written and verbal communication skills and the ability to collaborate within a team.

Nice To Haves

Exposure to Generative AI frameworks or libraries (e.g., LangChain, Semantic Kernel, OpenAI/LLM SDKs, vector databases).
Understanding of agentic design patterns, such as chaining, tool calling, memory, or task orchestration.
Exposure to cloud platforms, containerization (Docker), or orchestration tools (Kubernetes).
Familiarity with databases (relational or NoSQL) and basic data modeling concepts.
Ability to think analytically, break down complex problems, and propose practical solutions.
Strong sense of ownership, curiosity, and attention to detail.
Ability to work both independently and in a fast-paced, team-oriented environment.
Experience developing or consuming RESTful APIs or microservices.
Exposure to distributed systems, storage systems, or cloud-native architectures.
Familiarity with CI/CD pipelines, automated testing, or DevOps practices.
Experience working with large-scale codebases or production systems.
Interest in building software that leverages Generative AI, intelligent agents, and automation to improve developer and customer experiences.
Ability to understand business requirements and translate them into scalable technical solutions.

Responsibilities

Design, implement, and test software components in a collaborative, agile development environment.
Write clean, maintainable, and efficient code following established engineering best practices.
Leverage AI-powered developer copilots to accelerate coding, testing, debugging, and documentation tasks.
Participate in code reviews to both learn from and contribute to the team’s shared codebase.
Debug, troubleshoot, and resolve software defects and performance issues.
Work with senior engineers, architects, and product managers to understand requirements and translate them into technical solutions.
Assist in building or integrating Generative AI–powered features, such as intelligent assistants, automation workflows, or recommendation systems.
Gain exposure to agentic frameworks and patterns (e.g., tool-using agents, multi-step reasoning, orchestration of AI agents).
Contribute to documentation, design notes, and technical specifications.
Assist with automation, tooling, and continuous integration/continuous deployment (CI/CD) efforts as needed.
Communicate progress, challenges, and results clearly to both technical and non-technical stakeholders.