Senior Backend Engineer

The posting, as Citizen wrote it

A NOTE FROM THE FOUNDER

Citizen is a pipeline before it is an app. Signal comes in from every major American city, gets detected, verified, written, and delivered to the right people in seconds, and the whole thing has to hold when a million people open the app at once because something is happening. For years that took a large backend team. Now I build with agents and so do the engineers here, and a small group working that way out-ships teams five times the size. I want a backend engineer who is exceptional at the craft, runs agents like a second pair of hands, and treats a wrong alert as a bug with consequences. If that is you, come build the real-time system for the next chapter, next to me.

ABOUT

Citizen is the #1 safety app in the U.S. Every day, thousands of videos are captured live at the scene of real incidents and distributed in real time to people in every major American city. No other consumer product has this. It is a live network, a newsroom, and a safety tool at once, and it is growing again.

Underneath it is a real-time system: ingest from 911 radio, CAD feeds, user video, and partner feeds; detection, verification, and geolocation; distribution to millions of devices in seconds; the live video infrastructure that carries the scene to the app; and the enterprise products and API that deliver the same intelligence to cities, hospitals, campuses, and private security. You will own core pieces of that system and ship them with a small team of engineers, human and agent.

You will also build for the people inside Citizen who run the city. Our Mission Control and real-time operations team lives in our internal operating tools all day. A meaningful share of backend work is tooling for them, and they are the most demanding users you will have.

WHY NOW

Citizen is being rebuilt as an AI-native company, and the backend is where most of the rebuild happens. AI now sits in the pipeline itself, detecting and verifying incidents and deciding what people see, and the system has to get faster, more accurate, and cheaper per incident while it does. The enterprise business is working and needs to scale on the same platform. That is a very large amount of interesting work for a very small number of people who use agents to carry it.

HOW WE WORK

Every role at Citizen is two things: the craft, and the operation of AI to multiply it.

You are a backend engineer first. Distributed systems judgment, taste in code, and the instinct to know where a real-time system will break before it does. You are also the person who runs agents to write, review, test, and operate the code alongside you. You propose where agents run alone; production gates are policy, because this is a safety product. You hold the bar on correctness and you keep the hard calls for yourself. If in month three you are still hand-writing CRUD, migrations, or runbooks, something has gone wrong.

How work is organized. Engineering runs on a driver and builder model. Ever
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WHO YOU ARE

• You have built and run backend systems at consumer scale, real-time or event-driven, and you can point to the services you personally owned and what happened when they broke.
• You are fluent in Go, comfortable in Python for our data pipelines, and at home on Kubernetes and a modern cloud stack: message queues, relational and analytical stores, observability.
• You have carried a pager for a system people depended on, and you have a story about the worst night.
• You have worked on live video or streaming infrastructure, or you want to and can show you learn systems like it fast.
• You build with AI already. You have replaced whole parts of your own workflow with agents, you have opinions about where they fail, and you are paying attention to what is next. This is not a nice-to-have. It is the job.
• You measure. You instrument before you argue, and you know the difference between an event that fired and an event that landed in the warehouse.
• High agency. Handed a direction, you come back with a better one. You want to drive, not only build.
• You care about the mission. Safety is a real thing that happens to real people on their worst day, and you build the system like it matters.
• You want to be in New York, in the office, every day. The job does not work any other way.
• Bonus: You have put ML models or LLMs into a production path and you know the difference between a demo and a system with evaluation, fallbacks, and audit.

COMPENSATION

Base salary of $200,000–$260,000 per year, plus equity.

Compensation here is deliberately above market. The new normal is one person, working with agents, carrying what an engineering team used to carry. That person is rare, and we pay for the person, not the band. Meet the bar and we will comp you accordingly, in salary and in equity. We would rather one person own a real piece of Citizen than eight own a slice each. Full numbers in the first conversation.