Agentic AI, LLM Evaluation, and Trustworthy Systems Research Internship

Agentic AI, LLM Evaluation, and Trustworthy Systems Research Internship

Here at Siemens, we take pride in enabling sustainable progress through technology. We do this through empowering customers by combining the real and digital worlds. Improving how we live, work, and move today and for the next generation! We know that the only way a business thrive is if our people are thriving. That’s why we always put our people first. Our global, diverse team would be happy to support you and challenge you to grow in new ways.

Siemens Research & Predevelopment (RPD) is the central R&D department of Siemens and thus has a key role to shape the future of our products. RPD acts as a strategic partner to support the executive units of Siemens. In consequence the main research focus is on future technologies for industry, infrastructure, mobility, and healthcare. In this context, we are looking for an Intern that supports our Software Systems and Processes team in Princeton, NJ by researching and developing scalable intelligent systems using LLMs and semantic technologies.

Transform the everyday with us!

Are you passionate about ensuring the reliability and robustness of cutting-edge AI systems? We're looking for an innovative PhD intern to join our team and contribute to groundbreaking research focused on implementing a Verification and Validation (V&V) framework for multi-agent systems.

Modern software is rapidly moving from static applications to agentic AI systems that plan, reason, call tools, coordinate across agents, and adapt over multiple steps. As these LLM-powered systems enter industrial workflows, the critical challenge is no longer only building capable agents—it is evaluating, verifying, and validating that they behave reliably, safely, and transparently in complex, uncertain environments. In this internship, you will research and prototype next-generation methods for LLM and multi-agent system evaluation, including benchmarks, guardrails, f...