The intern will lead the development of an internal AI agent designed to increase the efficiency and consistency of technical support provided to the sales team and customers.
Responsibilities include: Using internal technical documentation to train and configure an agentic AI system.
Learning how to structure, manage, and refine data sources for AI use.
Testing the agent against real technical inquiries and validating outputs with Applications Engineering staff.
Iteratively improving the agent’s performance by adjusting inputs, refining data, or enhancing the model’s knowledge base.
Documenting processes, findings, and recommendations for long-term scale and support.
Conduct a detailed engineering data analysis project focused on MP battery weights, aiming to establish a standardized process and implement quality checks within the Richmond manufacturing plant’s SAP environment.
Responsibilities include: Learning the engineering attributes and configuration elements of MP battery products.
Handling and analyzing large datasets related to product weights and manufacturing attributes.
Applying sound statistical methodologies to identify trends, anomalies, and process improvement opportunities.
Collaborating with Applications Engineering, Operations, and IT to design and integrate new process checks into SAP.
Supporting documentation, data validation, and change management steps for SAP updates.

Actively pursuing a Bachelor’s degree in Electrical Engineering (or related engineering discipline).
Experience or coursework in:
Data analysis and statistical methods
Computer programming (Python, MATLAB, or similar)
Engineering problem-solving
Strong analytical skills and attention to detail.
Curiosity, initiative, and willingness to learn new tools and concepts.
Preferred:
Experience with large datasets or database querying.
Familiarity with AI/ML concepts or projects.
Exposure to SAP or similar ERP systems.

Applications Engineering Intern

Key skills