Senior Backend Engineer
Citizen · New York City
About this role
## Senior Backend Engineer — Citizen ### About Citizen 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. Underneath it is a **real-time system** that ingests and processes signals from: - 911 radio, CAD feeds, user video, and partner feeds - detection, verification, and geolocation - distribution to **millions of devices in seconds** - live video infrastructure that delivers the scene to the app - enterprise products and APIs that deliver the same intelligence to cities, hospitals, campuses, and private security ### Why now Citizen is being rebuilt as an **AI-native company**. AI now sits in the pipeline—detecting and verifying incidents and deciding what people see—so the system must become **faster, more accurate, and cheaper per incident** while scaling. ### How we work Every role is two things: 1. **Craft** (backend engineering excellence) 2. **Operation of AI** (using agents to multiply output) You’ll be a backend engineer first, with strong judgment for distributed, real-time systems—plus the ability to **run agents** as a second pair of hands to write, review, test, and operate code. > A wrong alert is treated as a **bug with consequences**. Engineering runs on a **driver + builder** model: - Drivers own scope, sequencing, and tradeoffs - Drivers are not assigned by seniority—drivers are the people who want the decision and responsibility ### On-call Citizen runs around the clock. - Rotational program: **~1 week every two months** - When you carry the pager: **24/7 availability** for urgent emergencies - Resolution expected in **hours, not days** ### What you will own You’ll own core pieces of the system and ship them with a small team (human + agent). Current areas include: - **Real-time pipeline**: ingest → detection/verification/geolocation → distribution - Key metrics: **correctness, latency, cost per incident** - **Live video infrastructure**: ingest from phone/restreamer and deliver to every viewer - Key metrics: cost + latency under load - **AI in the pipeline**: evaluation, provenance, guardrails, and staged human-in-the-loop → autonomous operation behind audited gates - **Internal operator tooling** (Mission Control backend): tooling that verifies, writes, and publishes incidents - **Enterprise / API / MCP / partners**: services behind enterprise consoles, public API + MCP access, and partner integrations - **Infrastructure & cost**: Go/Python services on Kubernetes with observability for a small team running a large system You’ll also contribute to: - **Instrumentation**: analytics events, warehouse validation, and ensuring leadership metrics match reality - **Agent loop**: extend and operate the agents that draft/review/test/operate backend code; raise the output bar ### Your first 90 days - **Days 1–30**: read code; use the product daily in New York; sit in Mission Control during live incidents; ship to production in week one; shadow on-call; identify the first three likely failure points - **Days 31–60**: drive your first initiative end-to-end; land a measurable improvement in latency/correctness/cost; take your first solo on-call week; propose the first agent loop to run without a human (test generation, review, or triage) - **Days 61–90**: ship an AI-in-pipeline capability / video improvement / enterprise service to real users; present a roadmap with the num
Listing freshness
CronJobs last confirmed this listing 1h ago. If its source stops confirming the opening for seven days, this page is removed from active inventory.