The opportunity
DeepL is a global AI product and research company focused on building secure, intelligent solutions to complex business problems. Over 200,000 business customers and millions of individuals across 228 global markets today trust DeepL's Language AI platform for human-like…
What you'll do
A "0-to-1" Builder Mindset: You thrive in ambiguity. You don't need a roadmap to build; you need a problem. You are comfortable prototyping a new feature in the morning and refactoring it for scale in the afternoon.
Product Obsession: You care about the flow of the conversation. You understand that "99% accuracy" means nothing if the audio arrives 3 seconds late. You optimize for the human experience.
Ship End-to-End Features: Build and deploy impactful features across the entire stack, from high-performance frontend UIs to streaming audio services on the backend and AI inference integration.
Tackle Real-Time Complexity: Debug and resolve challenging edge cases unique to real-time communication, including sub-second latency spikes, transcript flicker, audio glitches, and unstable network environments.
Collaborate Cross-Functionally: Partner closely in a tight-knit, cross-functional squad alongside PMs, Product Designers, and AI Researchers to scope, shape, and solve hard product and technical challenges.
A "Product-First" Mindset: You care deeply about the customer journey. You ask, "How does this feature help us close the next Enterprise deal?" before writing code.
What they're looking for
- Full-Stack Fluency: You're comfortable across the stack — building polished, modern UI in React and TypeScript on the frontend, and shipping backend services in Node.js/TypeScript (or a strongly transferable language, with willingness to ramp) on the backend.
- Real-time: WebRTC, WebSockets, streaming architectures, latency-sensitive systems.
- High Agency: You don't wait for permission. If the billing reconciliation: process is slow, you automate it. If the documentation for the API is unclear, you fix it.
- AI-Native Velocity: You leverage AI-powered tools (like GitHub Copilot or Claude) to accelerate your velocity and eliminate repetitive toil. You use AI for boilerplate code, test generation, and debugging, allowing you to focus your cognitive energy on high-value architectural decisions and complex problem-solving.
