AI Software Engineer I

Autonomous Solutions • Logan, UT

12d

About The Position

At ASI, we are revolutionizing industries with state-of-the-art autonomous robotics solutions. Within the fields of agriculture, construction, landscaping, and logistics, we deliver technologies that enhance safety, productivity, and efficiency. With our core values of Simplicity, Safety, Transparency, Humility, Attention to Detail, Autonomy and Growth guiding everything we do, we're shaping the future of automation in dynamic markets. As an AI Software Engineer I at ASI, you are responsible for supporting the development of internal AI-powered tools and applications under direct supervision. You contribute to front-end and back-end development tasks, assist with integration work, and build foundational skills shipping functional software within the internal platform.

Requirements

• Bachelor's degree in Computer Science, Software Engineering, or related field.
• 0-2 years of experience in full-stack software development.
• Familiarity with front-end frameworks such as React, Vue, or Angular.
• Exposure to back-end development using Node.js, Python, or similar languages.
• Basic understanding of cloud platforms (AWS, Azure, or GCP).
• Familiarity with version control workflows using Git.
• Exposure to AI/ML APIs or large language model (LLM) integration patterns.

Responsibilities

• Build front-end components and back-end services for internal applications following established architectural patterns.
• Assist in scaffolding and configuring new tools and prototypes within the internal AI platform.
• Support implementation of authentication flows, API wrappers, and access control features under supervision.
• Document tool usage, configuration steps, and onboarding materials to support team adoption.
• Participate in code reviews to receive feedback and develop software quality practices.
• Apply modern AI development frameworks, large language model (LLM) APIs, and integration patterns under guidance.
• Identify and escalate bugs, performance issues, and integration failures to senior engineers.
• Contribute to cloud deployment tasks on Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) under direction.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level