Senior Software Engineer
Company websitectgt.ai (CTGT, opens in new tab)
Base salary $175K to $250K
Employer-published annual base salary, USD. Advertised base range in San Francisco, CA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSan Francisco, CA
- WorkplaceOn-site
- Status at last checkSource accepting applications when checked
- Last checked (3 h ago) · observed since
About this job
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
Our Stack
Languages: Python, Rust, and Node/TypeScript, with React on the frontend
Data: Postgresql, vector, and graph databases
Infra: Docker, Kubernetes, Terraform, across several cloud providers and customer VPCs
ML: Self hosted models on multiple GPU providers and frontier APIs
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.
Source: CTGT on Ashby · View original posting (opens in new tab)
Pay in context
This role's base floor ($175,000) is above 48% of the 4,300 Software Engineering roles in California listed on this site; 57 others list the same floor. Their median floor is $176,000; the middle half runs from $149,100 to $204,000.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 6, 2026.
This listingSenior Software Engineer$175K to $250K
Machine Learning Engineer: LLM Interpretability & Systems$175K to $250K
Chart as a table
| Role | Published base |
|---|---|
| Senior Software Engineer (this listing) | $175K - $250K |
| Machine Learning Engineer: LLM Interpretability & Systems | $175K - $250K |
Observed changes
- Began meeting the published-salary criteria
- First observed on the employer's board
- Observed since
- Employer-stated posting date
- 2026-04-28
Where this pay comes from
Location as the employer wrote it: San Francisco
USD 175,000 – 250,000 · 1 YEAR · Salary
- Method
- Structured pay field published by the employer
- Checked
- Rule set
- us-base-v2
The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
