From Promega's posting. “We” and “our” refer to the employer.
OUR TEAM:
The Operations Engineering organization is made up of Process, Automation, Mechanical, Sustaining, and OT Engineers supporting manufacturing and product finishing operations across multiple campus buildings. Our teams also include several co-ops each year. This role works closely with the engineering leadership team and engineers across those disciplines. Operations Engineering regularly collaborates with other internal partners such as Quality, IT, Facilities, and Manufacturing.
YOUR ROLE:
As an AI Engineering Co-op, your role is to help build the knowledge layer infrastructure and reusable workflows that support Operations Engineering's AI transformation. You will learn how engineers do their work, identify where better tooling and easier access to information would save meaningful time, and build, document, and support solutions the team can adopt and maintain after your term ends.
This is an eight-month, full-time co-op, and offers hands-on experience applying emerging AI technology to real problems in a regulated manufacturing environment.
YOUR EXPERIENCE:
We are looking for a naturally curious self-starter with excellent communication and documentation skills and a demonstrated ability to work in cross-functional teams to achieve our department and company objectives. Comfort talking with subject matter experts, asking good questions, and learning an unfamiliar technical domain quickly is essential. Experience or interest in Python, SQL, prompt engineering, and retrieval-augmented generation is important; experience in a regulated industry is a plus.
*This is an 8-month co-op position with two possible start dates in 2027: January through August, or May through December. Candidates must be able to commit to the full 8-month term for their selected timeline.
CORE DUTIES:
1. Meet with engineers and subject matter experts to learn how they work, where their time goes, and what makes information hard to find, then help translate those problems into practical solutions.
2. Help identify and prioritize use cases where better tooling or easier access to knowledge would save engineers meaningful time.
3. Build and organize knowledge layer content, including context files, structured documentation, and retrieval patterns that help AI tools surface accurate answers from Operations Engineering knowledge.
4. Prototype and test reusable workflows, then work with the team to refine them into solutions that are reliable enough for everyday use.
5. Document solutions clearly so engineers who did not build them can use, support, and modify them after the co-op ends.
6. Support adoption across the team through demonstrations, walkthroughs, quick reference guides, and hands-on help.
7. Capture recommendations on which solutions worked well and could be extended to other Manufacturing teams.
8. Learn the Operations Engineering domain, including process control systems, production workflows, root cause analysis methodology, and documentation requirements, in order to build solutions that fit how the work actually happens.
9. Assist with GMP documentation and tasks associated with engineering projects and knowledge management initiatives.
10. Demonstrates inclusion through their own words and actions and is accountable for a safe workspace. Acts with kindness, curiosity and respect for others.
11. Embracing and being open to incorporating Promega's 6 Emotional & Social Intelligence (ESI) core principles in daily work.
12. Understands and complies with ethical, legal and regulatory requirements applicable to our business.
13. Other duties and responsibilities as assigned.
EXPECTED OUTCOMES:
1. A small set of documented AI workflows in active use by the Operations Engineering team by the end of the co-op.
2. Improved knowledge accessibility, with engineers able to find technical answers faster and with less effort.
3. Reduced manual documentation effort on at least one recurring engineering task.
4. Training materials and reference guides that help engineers apply new capabilities to their own work.
5. Written recommendations on which solutions are worth extending to other Manufacturing teams.
KEY QUALIFICATIONS:
1. Currently enrolled in a Bachelor's degree program in Systems Engineering, Industrial Engineering, Computer Science, Data Science, Machine Learning or other Engineering with an AI specialty, or a related field, and able to commit to an eight-month full time co-op (January through August or May through December).
2. Naturally curious and interested in understanding how engineers work, and how AI tools can be applied to engineering, with an ability to connect what people describe to how a solution should be built.
3. Comfortable talking with subject matter experts, asking questions, and learning an unfamiliar technical domain quickly.
4. Experience or interest in Python, including scripting and working with APIs.
5. Experience or interest in SQL and organizing data.
6. Experience or interest in prompt engineering, retrieval-augmented generation (RAG), and working with large language models.
7. Willing to experiment with emerging AI tools and iterate when a first attempt does not work.
8. Strong organization, communication, and documentation skills, including the ability to explain technical work to people who are not specialists.
9. Self-starter who can manage multiple priorities and ask for direction when needed.
10. Proficiency with Microsoft 365 applications (Word, Excel, PowerPoint, Teams).
11. Awareness of or interest in learning regulatory and compliance concepts in a manufacturing environment.
PREFERRED QUALIFICATIONS:
1. Coursework, personal projects, or prior internship experience with generative AI platforms (e.g., Azure OpenAI, OpenAI API, Claude).
2. Familiarity with Git and collaborative development practices.
3. Experience building or documenting software solutions and technical workflows.
4. Experience teaching, tutoring, or helping others adopt a new tool or process.
5. Exposure to Databricks, Power BI, or similar analytics tools.
6. Coursework or exposure to manufacturing concepts, process control systems, or production environments.
7. Experience with knowledge management systems, SharePoint, or similar platforms.
PHYSICAL DEMANDS: 1. Ability to remain stationary for several hours at a time.
2. Ability to use a computer workstation and Microsoft 365 applications.
3. Ability to work in an office environment.
4. Ability to traverse between campus locations as needed for meetings and training.
5. Occasional ability to observe equipment and operations in a production or lab environment.
At Promega, we value diversity and strive to create an inclusive workplace. We are proud to be an Equal Opportunity Employer, making employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability, or any other protected class.
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