AI-Native Development Platform Engineer Intern, MS - Summer 2027
About The Position
The Engineering Applications team in Marvell IT builds and runs the platforms Marvell's engineers use every day — DevOps and CI/CD infrastructure, custom engineering applications, and the AI layer that ties them together. We build and operate Marvell's governed AI platform, which answers questions and takes action across multiple engineering systems, and an agentic SDLC platform that carries a feature from requirements through to deployment with humans approving every decision. Day to day we design, build, deploy and support these services on AWS with modern CI/CD, and we partner directly with engineering teams to replace manual, multi-tool handoffs with automated, governed workflows. As an intern on this team you will ship production software that engineers across Marvell use — applying agentic AI to the real software development lifecycle, not a sandbox.
Requirements
- Currently pursuing a Bachelor's or Master's Degree in Computer Science, Computer Engineering, Software Engineering or a related field with an expected graduation date between Fall 2027 – Summer 2028
- Proficiency in at least one modern programming language such as Python, C#, Java or TypeScript/JavaScript, with the ability to write and debug production-quality code.
- Working knowledge of Linux and Git-based version control, including branching, pull requests and code review workflows.
- Familiarity with CI/CD concepts and tools (GitHub Actions, Jenkins or similar) and with containerization using Docker or Kubernetes.
- Hands-on exposure to LLM or agentic AI development — prompt design, model APIs/SDKs, retrieval-augmented generation, or AI-assisted coding tools such as Cursor, Claude Code or Copilot.
- Demonstrated ability to take an ambiguous problem to a working result independently, communicate progress clearly and present technical outcomes to an audience.
Nice To Haves
- Experience building REST APIs or system integrations against tools such as Jira, GitHub, Jenkins, Confluence or ServiceNow.
- Exposure to cloud platforms (AWS, Azure or GCP) and to deployment tooling such as Helm, Argo CD or Terraform.
- Familiarity with Model Context Protocol (MCP), agent orchestration frameworks such as LangGraph, or multi-agent workflow design.
- Experience with relational databases (SQL Server, MySQL or PostgreSQL) and with front-end frameworks such as React.
Responsibilities
- Build and ship one feature end-to-end on our agentic AI platform for the software development lifecycle, from design through production deployment.
- Develop integrations and MCP-based tooling that connect AI agents to real engineering systems such as Jira, GitHub, Jenkins, Confluence and AWS.
- Automate build, test and deployment workflows using CI/CD pipelines (GitHub Actions, Jenkins) and containerized deployments on Kubernetes/EKS.
- Write and review code alongside senior engineers using AI-assisted development tools including Cursor and Claude Code, held to the team's normal quality and review standards.
- Instrument and measure the impact of what you build — adoption, performance and engineering time saved — and present the results back to the team.
- Collaborate with engineers, program managers and IT partners to scope the project, gather requirements and pilot the feature with real users.
Benefits
- medical, dental, and vision coverage
- perks and discounts
- robust mental health resources to prioritize emotional well-being
- paid holidays
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What This Job Offers
Career Level
Intern
Education Level
No Education Listed
