Data & AI Intern - Summer 2027

Haag, a Salas O'Brien Company•,

1d•$22 - $27•Remote

About The Position

As a Data & AI Product Engineer Intern, you will support the development of data pipelines, models, and applications that power practical Data & AI products. You will contribute to real product work while learning established platform patterns, engineering practices, and quality standards. This hands-on internship provides experience working on real business problems alongside experienced engineers. You will have opportunities to build Python and SQL skills, learn modern data and AI technologies, and see how solutions move from an idea through development and testing. You will be part of a small product pod, working with a Product Manager and engineers to deliver and improve useful, reliable products. The role reports to the Data & AI Product Manager for the assigned product, with technical guidance and support from engineers on the product pod. You will work on defined projects and backlog items with guidance; the scope may grow as you become more familiar with the platform, products, and engineering practices. Work is driven by a prioritized product backlog and often begins with a business problem. You will work with the product pod to understand the need, contribute to a solution, and learn how Data & AI products are developed and improved over time. As you build your skills and demonstrate greater independence, you may take on broader or more complex assignments.

Requirements

Currently pursuing a bachelor’s or master’s degree in computer science, data science, engineering, mathematics, information systems, or a related discipline.
Foundational knowledge of Python and SQL through coursework, projects, previous internships, or other experience.
Basic understanding of databases, data structures, data modeling, software development, or related concepts.
Strong problem-solving skills and attention to detail.
Ability to learn new technical concepts and apply feedback.
Ability to communicate progress, questions, and challenges clearly.
Interest in data engineering, machine learning, artificial intelligence, or software development.
Interested in building practical solutions and seeing how technology is applied to real business problems.
Curious and willing to ask questions when something is not understood.
Enjoys learning new technologies and applying what has been learned.
Interested in both the business problem and the technology used to solve it.
Welcomes feedback and enjoys working collaboratively with others.

Nice To Haves

Coursework or project experience involving Python, SQL, data engineering, machine learning, or software development.
Exposure to cloud data platforms or distributed data processing.
Familiarity with version control tools such as Git, including basic concepts such as branches, commits, and pull requests.
Exposure to Databricks, Delta Lake, or Unity Catalog.
Coursework, projects, or personal experience involving machine learning or generative AI.
Experience developing a technical project individually or as part of a team.

Responsibilities

Assist with building and maintaining data pipelines, including ingestion, transformation, data quality checks, and monitoring.
Contribute to product features through coding, testing, documentation, and troubleshooting.
Support machine learning or generative AI components when they are part of the product roadmap.
Write and test Python and SQL with guidance from experienced engineers.
Learn and follow established platform patterns, engineering standards, and development practices.
Participate in code reviews to learn from feedback and develop stronger engineering practices.
Help investigate defects, data quality issues, and other technical problems.
Support testing and evaluation to help determine whether data and AI solutions are working as intended.
Participate in product pod discussions to better understand business requirements and technical decisions.
Maintain documentation for the components, processes, and projects you support.