Product Engineer (f/m/x)

Job description

Cologne, Germany (Hybrid) Team: Product & Engineering · Reports to: CTO · Format: Full-time, permanent Own a piece of the product, not a ticket queue ilert is the alerting, on-call and incident response platform that engineering teams worldwide rely on when things break. That covers alerting, on-call scheduling, call routing, status pages, and an AI SRE that investigates incidents alongside the people responding to them. We're bootstrapped, profitable, and small (~15 engineers). Your work reaches customers fast, and you have a real say in what gets built. We're looking for a Product Engineer to own one area of that product. We'll give you a domain, not a spec. You figure out what customers need, build it across the stack, ship it, and check whether it made a difference. We build with AI every day. But AI is leverage on top of engineering, not a substitute for it. We're looking for a solid engineer first, someone who uses AI to move faster, not to skip understanding the code. Tasks Own a product domain end-to-end. Depending on where you'll have the most impact, that could be alerting, on-call and call routing, status pages, integrations, or our AI SRE. You propose what to build, build it, and measure whether it worked. Ship across the stack. Java and Rust on the backend, React and TypeScript on the frontend. We work in 2-week bets that end in a production deploy. Talk to customers. Join customer calls, read support conversations, dig into usage data, and turn what you learn into product improvements. Make the scope calls. Decide what to cut, what ships first, and what to validate before building it. We trust you with these trade-offs. Own it in production. You're responsible for what you ship, including when it breaks. Reliability is literally our product. What you bring 2+ years of software engineering in a team codebase. That means code review, tests, production incidents, and code you didn't write alone. Side projects are great, but they don't replace this. You've shipped features end-to-end and cared whether people actually used them. Comfortable across the stack. Strong on one side, and willing and able to work on the other. Solid fundamentals. Data modeling, debugging, testing, and thinking through failure modes. You can read unfamiliar code and reason about it before you reach for a prompt. Real AI fluency. You use AI coding tools every day, you know…