Backend Engineer, Applied AI

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 ProtectOS and Regulator, 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. Every initiative is a drive with one accountable driver who owns scope, sequencing, and tradeoffs, and a small set of builders who ship it with them. Drivers are not assigned by seniority; they are the people who want the decision and the responsibility that comes with it. You will build on other people’s drives and you will drive your own, early.

On-call. Citizen runs around the clock and so does the backend. On-call is a rotational program: roughly one week every two months, and when you carry the pager you are available 24/7 for the most urgent emergencies, with resolution expected in hours, not days. Everyone on the team carries it. Say now if that is not for you.

What You Will Own

We are not hiring a caretaker for the whole backend. We are hiring someone dedicated, who wants ownership and can carry it, over a real piece of the core system, chosen by the team’s need first and your interest second, and who is equally willing to own new ideas and new services where they move the company’s growth and current focus. The pieces on the table today:

The real-time pipeline. Ingest from 911 radio, CAD feeds, user video, and partner feeds; detection, verification, geolocation, and distribution to millions of devices in seconds. Correctness, latency, and cost per incident are the three numbers.

Live video infrastructure. Ingest from the phone, the restreamer, and delivery through Mux to every viewer. One of the largest cost and latency …