Graduate Software Engineer, AI Product Engineering

Caselle•Provo, UT

11d•Hybrid

About The Position

Govineer is looking for an early-career software engineer with a computer science foundation who wants to build AI-enabled products that customers actually use. You will work with experienced engineers and product leaders across the full stack: user experience, APIs, data, model integration, evaluation, and production reliability. You will have room to experiment and a responsibility to turn promising ideas into dependable software.

Requirements

A recent degree in computer science, computer engineering, or a related field, or equivalent practical experience.
Solid programming fundamentals and experience building at least one working application or substantial technical project.
Familiarity with one frontend framework and one backend language, plus APIs, databases, version control, and testing basics.
Interest in AI/ML and practical curiosity about model APIs, data quality, evaluation, and responsible use. Prior professional AI experience is not required.
Strong learning habits, collaborative communication, and care for the people using the software.

Nice To Haves

You ship well-tested features, contribute to useful AI experiments, learn to own small product problems end to end, and improve the quality of the team around you.

Responsibilities

Build and improve customer-facing features across frontend, backend, APIs, and data services.
Help make public-facing experiences accessible and internal workflows accurate, secure, and easy to audit.
Prototype AI-assisted workflows, then help evaluate whether they are accurate, useful, safe, and worth operating in production.
Write readable code, tests, documentation, and instrumentation; review code and learn from feedback.
Work with product managers, designers, and customers to understand the problem before choosing a technical approach.
Help build reusable services that can connect new products with established Govineer applications.
Investigate defects and production behavior, and use what you learn to improve the product.