What are the responsibilities and job description for the Instructional Staff - AI Engineer position at Carnegie Mellon University?
Description
Position Title: Instructional Staff - AI Engineer
Location: Heinz College, Carnegie Mellon University
Start Date: August 24, 2026 (Fall Semester)
Position Type: Part-Time, Temporary
Reports To: Faculty Supervisor(s)
Student-Facing: Yes
Position Summary
Heinz College at Carnegie Mellon University is seeking a graduate of the Master of Artificial Intelligence Systems Management (AIM) or an AI-related CMU program to assist in creating AI systems or workflows for assignments originally designed for Python developers into equivalent assignments for AI systems or LLM agent workflows. This role supports curriculum development and delivery for these courses, which include core courses in the AIM program and a related MISM course: 95-820 NL(X) and LLMs, 94-844 Generative AI Lab, 95-864 AI Model Development, and 94-879 Fundamentals of Operationalizing AI.
Key Responsibilities
Manage software, data and AI model compliance, including understanding university, local, state and federal policies to ensure course content, computing environments, computer resources, data, information and course delivery meets university, local, state and federal rules.
Establish, develop and maintain shared compute resources, such as virtual machines or local hosts, for implementing and evaluating Generative AI models.
Develop course assignments and activities to teach Generative AI model development, evaluation, operationalization, and standard industry practices for AI engineering.
Translate existing Python programming assignments into LLM Agent or 'Agentic AI' equivalents.
Collaborate with a supervising professor to align assignments with course objectives.
Maintain clear documentation of decisions and code structure.
Assist in testing and validating translated assignments for correctness and usability.
Additional Information
This is a student-facing, full-time temporary role focused on backend curriculum support.
The position is ideal for someone looking to contribute to academic development while gaining experience in educational technology and instructional design.
This is an AI-engineering focused position, supporting AI courses at Heinz College, Carnegie Mellon University. The position is ideal for someone who enjoys building systems, workflows or APIs for large language model (LLM) systems.
Qualifications
Required Qualifications
Graduate of the AIM program at Heinz College, Carnegie Mellon University.
Willingness to present or communicate with students on a regular basis.
Proficiency in Python programming language and LLM System Engineering.
Experience establishing virtual machine and compute environments (Linux, AWS, Google Cloud Platform).
Strong understanding of distributed AI system concepts and infrastructure.
Experience with designing and conducting LLM evaluations and working with LLM APIs.
Ability to work independently and communicate effectively with faculty supervisor(s).
Ability to conduct worth with integrity and ethics and work professionally with students.
Preferred Qualifications
Experience with educational content development or curriculum support.
Experience with version control systems (e.g., Git).
Experience working with containers (Docker, Podman, Apple Containers)
Attention to detail and commitment to producing high-quality instructional materials.
Position Title: Instructional Staff - AI Engineer
Location: Heinz College, Carnegie Mellon University
Start Date: August 24, 2026 (Fall Semester)
Position Type: Part-Time, Temporary
Reports To: Faculty Supervisor(s)
Student-Facing: Yes
Position Summary
Heinz College at Carnegie Mellon University is seeking a graduate of the Master of Artificial Intelligence Systems Management (AIM) or an AI-related CMU program to assist in creating AI systems or workflows for assignments originally designed for Python developers into equivalent assignments for AI systems or LLM agent workflows. This role supports curriculum development and delivery for these courses, which include core courses in the AIM program and a related MISM course: 95-820 NL(X) and LLMs, 94-844 Generative AI Lab, 95-864 AI Model Development, and 94-879 Fundamentals of Operationalizing AI.
Key Responsibilities
Manage software, data and AI model compliance, including understanding university, local, state and federal policies to ensure course content, computing environments, computer resources, data, information and course delivery meets university, local, state and federal rules.
Establish, develop and maintain shared compute resources, such as virtual machines or local hosts, for implementing and evaluating Generative AI models.
Develop course assignments and activities to teach Generative AI model development, evaluation, operationalization, and standard industry practices for AI engineering.
Translate existing Python programming assignments into LLM Agent or 'Agentic AI' equivalents.
Collaborate with a supervising professor to align assignments with course objectives.
Maintain clear documentation of decisions and code structure.
Assist in testing and validating translated assignments for correctness and usability.
Additional Information
This is a student-facing, full-time temporary role focused on backend curriculum support.
The position is ideal for someone looking to contribute to academic development while gaining experience in educational technology and instructional design.
This is an AI-engineering focused position, supporting AI courses at Heinz College, Carnegie Mellon University. The position is ideal for someone who enjoys building systems, workflows or APIs for large language model (LLM) systems.
Qualifications
Required Qualifications
Graduate of the AIM program at Heinz College, Carnegie Mellon University.
Willingness to present or communicate with students on a regular basis.
Proficiency in Python programming language and LLM System Engineering.
Experience establishing virtual machine and compute environments (Linux, AWS, Google Cloud Platform).
Strong understanding of distributed AI system concepts and infrastructure.
Experience with designing and conducting LLM evaluations and working with LLM APIs.
Ability to work independently and communicate effectively with faculty supervisor(s).
Ability to conduct worth with integrity and ethics and work professionally with students.
Preferred Qualifications
Experience with educational content development or curriculum support.
Experience with version control systems (e.g., Git).
Experience working with containers (Docker, Podman, Apple Containers)
Attention to detail and commitment to producing high-quality instructional materials.