Senior Software Engineer, Platform

CTGTSan Francisco, CA

About The Position

CTGT is building governance infrastructure for frontier intelligence. Your job is to make sure it deploys effortlessly, runs reliably at scale, is easy to reason about under pressure, and delightful to build on. You will own the systems that connect our Policy Engine and core model work to production environments. That includes how services are structured, how they are deployed, how they are observed in production, and how they behave when things go wrong. This role sits at the boundary where most systems break. Between backend logic and infrastructure, between experimental systems and production guarantees. You are expected to operate comfortably in that space and improve it over time.

Requirements

  • Owned production systems and know what breaks under real load
  • Move comfortably between backend and infrastructure without treating them as separate domains
  • Strong experience with at least one major cloud platform
  • Use tools like Terraform as a means to control systems, not as an end in itself
  • Built observability that actually helps diagnose issues, not just dashboards
  • Take responsibility for system behavior and fix problems at the root

Responsibilities

  • Build and operate systems that serve AI workloads in critical business environments
  • Own how services are deployed, configured, and run across cloud and on-prem environments
  • Define infrastructure through code and enforce consistency across environments
  • Establish strong observability across the stack, including metrics, logs, and tracing that actually help debug real issues
  • Design deployment pipelines and runtime environments that support rapid iteration without breaking production
  • Work with ML engineers to turn experimental systems into reliable, production-grade services

Benefits

  • Competitive base compensation
  • Significant equity in a venture-backed company
  • Institutional investors including Google’s Gradient Ventures, General Catalyst, and Y Combinator
  • Work directly on the core systems that determine how models perform in the wild
  • Work ships into real, high-stakes environments where governance, audit-ability, and performance are non-negotiable
  • High degree of trust
  • Expected to form strong technical opinions and execute on them
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