Backend and Full-Stack Engineer

About the Role

We’re building AI-powered smart devices and connected-home experiences used by millions of people. As a Backend and Full-Stack Engineer, you’ll design and ship the services, APIs and web and app interfaces that connect devices, cloud and AI. You’ll work with Python and Node.js, collaborating closely with AI, firmware, mobile and QA teams to deliver fast, reliable and secure products at scale.

Key Responsibilities

• Design, build and maintain scalable backend services and REST/WebSocket APIs using Python and Node.js
• Develop full-stack features, including responsive web dashboards and admin tools, using modern frontend frameworks
• Integrate AI services such as LLM APIs, speech and vision pipelines, and vector databases into production systems
• Build secure device-to-cloud communication for pairing, media upload, settings sync and over-the-air updates
• Design efficient database schemas and optimize queries across SQL and NoSQL stores
• Write clean, tested and well-documented code; take part in code reviews
• Set up CI/CD, monitoring, logging and alerting with the DevOps team
• Troubleshoot production issues and improve performance, reliability and cost
• Follow best practices for data privacy and security, since our products handle sensitive audio and camera dataRequired Skills
• 3+ years of hands-on backend development in Python (FastAPI, Django or Flask) and Node.js (Express or NestJS)
• Strong fundamentals in data structures, algorithms and system design
• Experience building and consuming REST APIs; familiarity with WebSockets or event-driven systems
• Frontend experience with React (or similar), along with HTML, CSS and JavaScript/TypeScript
• Solid knowledge of databases such as PostgreSQL or MySQL, plus MongoDB or Redis
• Working knowledge of cloud platforms (AWS, GCP or Azure), Docker and Git
• Understanding of authentication and authorization (OAuth, JWT) and API securityGood to Have
• Experience integrating LLM APIs, prompt and context handling, or RAG pipelines
• Exposure to IoT or device-connected systems, MQTT or Bluetooth/Wi-Fi onboarding flows
• Kubernetes, message queues (Kafka, RabbitMQ) and infrastructure-as-code
• Experience with multilingual applications or speech and media processing
• Familiarity with automated testing (Pytest, Jest) and observability tools