## **About CTGT & The Mission**
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.
## **The Role**
CTGT's mission is to deploy high-performance model governance at enterprise scale. This places rigorous requirements on our system. Our Policy Engine must produce decisions that are correct, fast, and reliably auditable, you will ensure it stays that way as load grows and the platform expands into new environments. This standard is set everywhere in the system, not at a single layer: where governance decisions are computed and persisted, where correctness has to hold under concurrent load, and where early design choices either compound into leverage or into debt.
This role is for the engineer who owns the system. You will make the architectural decisions that shape how the platform evolves, and you will write the code that proves those decisions were right. The work rewards strong judgment about what to build, what to defer, and what to throw away. It demands the ability to hold a large system in your head and keep it coherent as it grows.
We are looking for someone whose strength is the fundamentals of software engineering, applied at the level of real systems. The engineer other engineers want next to them when something hard needs to be built correctly the first time.
## **What You Will Do**
* Design and build the core services, deciding how the system is decomposed, where state lives, and how components communicate
* Work wherever the problem leads, from data model to product surface
* Make deliberate tradeoffs across accuracy, consistency, availability, and latency
* Define the internal APIs and abstractions that determine system trajectory 6+ months out
## **Who You Are**
* You have built non-trivial systems and can speak honestly about what aged well and what did not
* You understand distributed systems tradeoffs well enough to make the right call for a given problem
* You are comfortable on both sides of the stack and choose where to work based on the problem
* You have strong opinions about software design and can defend them without being precious about them
## **What We Offer**
**Compensation & Equity**: Competitive base compensation, plus significant equity in a venture-backed company with institutional investors including Google’s Gradient Ventures, General Catalyst, and Y Combinator. We want people who think and act like owners.
**Real Impact:** You will work directly on the core systems that determine how models perform in the wild. Your work ships into real, high-stakes environments where governance, auditability, and performance are non-negotiable.
**Autonomy & Trust:** We operate with a high degree of trust. You are expected to form strong technical opinions and execute on them.
Visa sponsorship is offered for this role.
