Software Engineering Intern, Product & Developer Productivity - HP IQ

HP•San Francisco, CA

About The Position

HP IQ's Product Integrity & Developer Productivity team builds tools and systems to improve developer productivity and product quality at scale. The team is investing in agentic systems that automate complex workflows, including JIRA triage, root-cause analysis, test planning, and quality automation. In this internship, you will work with the hiring manager and team to design, build, and deploy agents that use pre-trained machine learning models to address real problems for developers and quality engineers. You will contribute to projects exploring how AI can improve the way software is built, tested, and maintained, and gain experience with agentic development and tools intended for use by developers.

Requirements

Currently pursuing or recently completed a bachelor's or graduate degree in Computer Science, Engineering, or a related field.
Solid understanding of coding fundamentals and comfort with at least one programming language, with the ability to learn new languages and frameworks as needed.
Familiarity with agentic systems, AI tools such as Claude Code or OpenAI, or using models in applications; deep machine learning expertise is not required.
Ability to break down complex problems, solve them independently, and recognize when to ask for help.
Willingness to question established processes and propose alternatives in an environment that values fresh thinking and continuous improvement.
Strong communication skills and the ability to explain reasoning and technical choices clearly.

Nice To Haves

Familiarity with software development workflows, quality assurance, testing practices, or developer tooling.
Experience building or working with automation tools or systems that improve workflow efficiency.
Exposure to or familiarity with JIRA, CI/CD systems, or testing frameworks.
Experience collaborating in cross-functional teams or with people from different technical backgrounds.
Understanding of or coursework in machine learning, AI, or agent systems.
Example projects demonstrating agentic thinking, such as personal projects using AI tools to automate tasks.

Responsibilities

Design, build, and iterate on AI-powered tools and workflows that improve engineering productivity.
Develop intelligent systems to automate software development, testing, debugging, or quality assurance processes.
Prototype and evaluate approaches for applying large language models and agentic AI to engineering challenges.
Collaborate with software engineers, machine learning engineers, product managers, designers, and other cross-functional partners.
Participate in technical design discussions, code reviews, and collaborative problem-solving sessions.
Analyze technical challenges, propose solutions, and contribute ideas to improve products, tools, and engineering workflows.
Build, test, and iterate on production-quality software while learning modern engineering best practices.
Present work, share technical learnings, and contribute to a collaborative engineering culture.