Senior Backend Engineer (Python/Go), Multilingual Intelligence & Resolution Automation (MIRA)

About Wolt At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we’re building the delivery of (almost) everything and you’ll find us in over 500 cities in 30 countries around the world. In 2022 we joined forces with DoorDash and together we keep on dreaming big and expanding across the globe. Working at Wolt isn’t always easy, but it’s definitely exciting. Here you’ll learn more, build more, and ship more than in most other companies. You’ll be challenged a lot, but also have a lot of fun on the way. So, if you’re a self-starter with drive and entrepreneurial spirit, this could be the ride of your life. At Wolt, world-class customer service isn’t an afterthought, it’s at the heart of everything we do 💙 We’ve built our reputation on delivering fast, thoughtful, and high-quality support, and we’ve done that by investing deeply in our own technology. Rather than just reacting to problems, we aim to solve them before our customers and partners even notice. Behind the scenes, that means building systems that scale globally, handle real-world complexity, and empower support teams to do their very best work. This is where the Multilingual Intelligence Resolution Automation (MIRA) team comes in. The team is on a mission to make customer support truly borderless. We’re building intelligent, AI-powered systems used across Wolt, DoorDash, and Deliveroo, including a real-time translation engine that supports seamless conversations across 20+ languages. Processing hundreds of requests per minute and powered by modern cloud infrastructure and state-of-the-art LLMs, this system enables borderless support and helps create experiences that feel natural, human, and native, no matter where you are in the world. And we’re only just getting started. 🚀 What you’ll be doing Design, build, and operate scalable backend services powering real-time, customer-facing systems Develop and evolve AI-powered translation capabilities using LLMs in production Help build the tooling and infrastructure needed to evaluate models across quality, latency, and cost Collaborate closely with product, applied science, frontend, and platform teams to turn complex support problems into robust user-facing systems Take ownership of technical decisions and help shape the architecture and future direction of the system Improve the performance, reliability, and operational readiness of services handling real production traffic Continuously explore better ways of working, including leveraging AI tools to improve development workflows Our humble expectations 👉 You have solid experience designing, building, and integrating quality software (microservices) at scale within a complex domain. 👉 You have strong backend development skills in Python or Go (interest in other tech is highly appreciated) 👉 You actively leverage modern AI tools (such as GitHub Copilot, Claude, ChatGPT or similar) to enhance your productivity, code quality, and day-to-day development workflow. 👉 You have strong technical leadership skills. 👉 You have experience with cloud platforms (AWS or similar), container orchestration (Kubernetes, Docker), observability tools (such as DataDog), and database technologies (SQL and NoSQL). 👉 Your stakeholder management skills are excellent. 👉 You're a pragmatic problem-solver with a growth mindset, eager to step outside your comfort zone and continuously learn. 👉 You're comfortable working with real-world data and its nuances. What we offer A chance to build something that truly matters, technology that enables people to connect and solve problems across languages and borders The opportunity to work with AI and LLMs in real, high-impact production use cases Flexibility to work from Helsinki or Tallinn (hybrid), or remotely within Finland or Estonia Being part of a global engineering organization of 2000+ people, we aim to build ... (truncated, view full listing at source)