Software Engineering Intern (Summer 2027)

Despite massive investment in commercial AI, organizations often find that demonstrated value is elusive, primarily due to the non-deterministic risk inherent to generative models. CTGT is the deterministic governance layer that enables the most important global institutions to deploy AI workflows with confidence.

Born out of Stanford University research, we provide the control plane that makes it possible. A lightweight, model-agnostic system that enforces policy, prevents drift, and produces auditable decisions in real time. When benchmarked on HaluEval, the CTGT Policy Engine (paired with GPT-120B OSS) outperformed frontier models (Gemini 3 Pro Preview, Claude 4.5 Opus and 4.5 Sonnet) at drastically lower compute cost.

While we sit on the edge of AI research, CTGT brings frontier intelligence into real-world environments. We apply cutting-edge theory directly in production to make large language models more reliable, controllable, and performant in practice.

Our mission is to bring models to the level of performance and accountability required by the Fortune 500. By bridging the gap between LLM capabilities and domain-specific requirements, we unlock the true potential of generative AI to solve the most pressing problems in our world today.

This is not a side project internship. You will own a meaningful piece of work end to end, ship it to a real system, and see it used. You will sit close to the engineers building the Policy Engine and the platform around it, and you will be expected to form opinions, ask hard questions, and take problems further than they were handed to you.

We are looking for someone whose strength is the fundamentals: someone who writes clean code, reasons carefully about correctness, and wants to understand the whole system rather than just the piece in front of them.