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.
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.
Ready to apply? Let us help you stand out.
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.
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.
CTGT is an applied AI research laboratory fundamentally solving the alignment and reliability bottleneck for enterprise AI.
For enterprises, especially highly regulated industries, deploying Generative AI is historically a compromise between capability and catastrophic risk. Standard enterprise approaches, such as RAG, fine-tuning, and prompt engineering, operate at the wrong abstraction layer. They are inherently probabilistic, carry massive engineering overhead, and fail to deliver the mathematical certainty required by the Fortune 500.
We focus on the science of representation engineering and have productized mechanistic interpretability. By opening the "black box" of neural networks, CTGT has developed a proprietary architecture that intervenes directly at the model's representation layer. We convert complex corporate SOPs, SEC/FINRA regulations, and strict editorial rulebooks into machine-readable "Policy as Code," enforcing deterministic constraints and defensible audit trails without requiring expensive model retraining.
The result is a step-function breakthrough in enterprise AI economics and capability. Our fundamental architecture allows organizations to run secure, self-hosted open-source models that mathematically match the reasoning and performance of frontier models. Benchmarks from our enterprise deployments demonstrate a 96.5% prevention of hallucinations, up to a 3.3× accuracy multiplier in complex domain-specific tasks, and an 80-90% reduction in human-in-the-loop manual review.
Backed by an $8M seed round from Gradient Ventures (Google), General Catalyst, and Y Combinator, CTGT is currently deployed with Fortune 500 companies, including Tier-1 financial institutions and global media conglomerates, giving them the deterministic control necessary to deploy enterprise AI with zero margin for error.
Salary
$175,000 - $250,000
Equity
0.5% - 1%
Location
San Francisco, CA, US
Experience
3+ years
