Startups · AI

Software Engineering Intern (Summer 2027)

CTGT · San Francisco · On-site

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About CTGT

Enterprise AI for where accuracy, speed, and compliance matter most. Backed by Y Combinator.

About the role

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.

What they're looking for

  • Pursuing a Bachelor's degree in Computer Science or a related technical field
  • Strong programming fundamentals and fluency in at least one general purpose language (Python and JavaScript are central to our stack)
  • Comfortable with Git and basic cloud workflows (AWS or GCP)
  • Able to explain technical ideas clearly to people with different backgrounds
  • Curious, self-directed, and able to make progress without constant scaffolding
More about this role

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...

Read the full posting on CTGT's site ↗

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