About The Position

Janitor is building AI interactive entertainment for millions of people. Its users create characters, worlds, stories, and relationships with AI. The engineer will build systems behind this experience, working on product features and the infrastructure that supports them. The company operates much of its own infrastructure and is investing further in it; this role will help decide what to build, how to run it, and where to simplify. The role combines backend engineering, product development, performance optimization, production reliability, and infrastructure scaling. It involves understanding systems from the user experience down to the machine, addressing issues that may appear as product bugs, slow pages, delayed jobs, websocket reconnects, or cache failures. The successful candidate will join a small team with substantial ownership over technical decisions and the opportunity to carry work through to production. Performance and reliability improvements can affect millions of users, who spend an average of more than 85 minutes a day on Janitor.

Requirements

  • At least four years of professional software engineering experience, with substantial work on backend systems or infrastructure.
  • Ability to follow a problem across services and layers, including unfamiliar parts of the stack.
  • Ability to make thoughtful tradeoffs and a preference for systems that are straightforward to understand and operate.
  • Ability to take an unclear problem, determine what matters, and carry a solution through to production.
  • Evidence of having built and operated substantial systems.

Nice To Haves

  • Experience with TypeScript/Node.js, NestJS, PostgreSQL, Redis, and Kubernetes is strongly preferred; experience with every tool is not required.
  • Experience with distributed systems or GPU infrastructure.

Responsibilities

  • Build backend services and product features connected to the AI stack.
  • Improve platform speed and efficiency.
  • Find bottlenecks across APIs, database queries, caching, background jobs, and real-time connections.
  • Own production reliability by investigating failures, fixing their causes, and improving deployment, monitoring, and recovery.
  • Help scale infrastructure by making practical architecture and capacity decisions as usage grows.
  • Understand systems from the user experience down to the machine and improve them.
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