AI Applications Engineer (Limited Term)

NorthStar Medical Radioisotopes; Beloit (WI); On-site; USD 95,000 - 135,000; Full time

Job summary

NorthStar Medical Radioisotopes is seeking an AI Applicants Developer (Limited Term) to design, develop, test, and deploy internal software tools using AI and automation. You will translate business requirements into scalable digital solutions and work closely with Process Excellence teams to validate performance on real-use cases.

The role emphasizes hands-on development, qualification for regulated environments, and deployment across teams, with a focus on improving operational efficiency and

Qualifications

• Bachelor's degree in Computer Science, Data Science, Information Technology, Engineering, or related field.
• Experience developing applications, automations, AI solutions, or data‑driven tools.
• Experience developing and deploying AI-enabled applications (not just models).
• Familiarity with large language models, prompt engineering, or AI orchestration tools.
• Exposure to regulated or quality‑controlled environments.

Responsibilities

• Design, develop, and deploy AI-enabled applications and tools per requirements.
• Collaborate with cross-functional teams to refine and iterate solutions.
• Evaluate and deploy new AI development tools and workflows.
• Deploy applications and support adoption across teams.
• Test, debug, and validate applications for reliability and performance.

Skills

AI development

Automation

Data-driven tools

Cross-functional collaboration

Education

Bachelor's degree in CS/DS/IT/Engineering

Tools

Power Platform

Azure

Job description

NorthStar Medical Radioisotopes is seeking an AI Applicants Developer (Limited Term) to design, develop, test, and deploy internal software tools using AI and automation. You will translate business requirements into scalable digital solutions and work closely with Process Excellence teams to validate performance on real-use cases.

The role emphasizes hands-on development, qualification for regulated environments, and deployment across teams, with a focus on improving operational efficiency and