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Engineered Arts, a leading manufacturer of full-size humanoid robots for entertainment, education, and communication, is seeking a mid-to-senior full stack developer to join their team in Montreal. The company has 20 years of hardware and software development experience, with robots deployed in over 30 countries and customers including NASA, PwC, and Meta. Their Ameca robot gained viral recognition as 'the face of AI,' and they're expanding into the service robot segment for applications like receptions, check-in desks, and information points.
You will build and maintain React/TypeScript applications across their cloud platform, focusing on fleet configuration, agent behavior, and real-time telepresence interfaces. You'll design and evolve GraphQL APIs and Python/Django backend services powering the platform, while developing on-robot Python services that bridge hardware, local behavior, and cloud configuration. A key responsibility is integrating and productizing LLMs and AI pipelines—including streaming, tool calling, RAG/knowledge bases, and multi-provider TTS/STT—to turn ambiguous agent behavior into clear product contracts with defined schemas, permissions, fallbacks, and observability.
You'll optimize AI-powered robot experiences for latency, cost, and robustness, building conversational experiences that feel natural on physical humanoids in real-world conditions, not just controlled demos. You'll debug issues spanning front-end, back-end, and on-robot layers, proactively improving testability and observability. Collaboration with product, UX, DevOps, QA, and embedded engineers is essential to turn requirements into shippable, high-quality designs. You'll also coach and support junior developers, raising the bar for quality across a complex, fast-moving codebase.
Required skills include mid-to-senior production experience as a full-stack developer, strong TypeScript and React for complex applications, strong Python backend experience (Django preferred), GraphQL API design and consumption, comfort with Linux systems and remote debugging, solid Git and CI/CD practices, relational database knowledge (PostgreSQL preferred), and demonstrated evidence of shipping features spanning UI, API, and external runtimes (device, edge, IoT, robot, etc.). Clear communication and collaboration across disciplines is essential.
The tech stack includes TypeScript, React, GraphQL, and Material-UI on the frontend; Python, Django, PostgreSQL, and WebSockets on the backend; async Python on Linux with LLM/TTS/STT integrations and RAG for on-robot/AI; and Docker, Kubernetes, and GitLab CI for delivery. Production experience with LLMs and related systems is a nice-to-have.
