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Cruq AI, an AI-native automation platform provider, seeks a Lead Engineer Robotics - Teleoperation & Data Capture Systems in Dubai. You will design, build, and optimize teleoperation and data workflows, integrating with Cruq AI's agentic stack.
The role combines hardware integration on-site with design and coding tasks remote, helping advance perception pipelines and secure reliable robot-AI connectivity. Ideal candidates will have strong robotics engineering background, experience with
Cruq AI is an AI-native automation platform that helps enterprises and scale-ups transform operations through specialized AI agents. Its modular AgentOS and extensive library of pre-built agents support end-to-end workflow automation across functions such as data entry, customer service, compliance, finance, HR, healthcare, IT, legal, and retail. The platform integrates seamlessly with existing enterprise systems, offering centralized management, advanced data handling, and retrieval-augmented generation capabilities. Cruq AI enables organizations to reduce operational costs, improve accuracy, and scale efficiently, backed by proven case studies and industry-specific solutions. The company focuses on continuous improvement and self-evolving agents to keep operations reliable and competitive.
As Lead Engineer Robotics - Teleoperation & Data Capture Systems, you will design, build, and optimize robotic teleoperation and data capture solutions that integrate with Cruq AI's agentic automation platform. In this full-time hybrid role based in Dubai, United Arab Emirates, you will spend part of your time on-site for hardware integration, experimentation, and team collaboration, with some work-from-home flexibility for design, coding, and documentation tasks. Day-to-day responsibilities include architecting teleoperation systems, developing control and perception pipelines, implementing data capture and labeling workflows, and ensuring reliable connectivity between robots, sensors, and AI agents. You will collaborate closely with product, AI, and infrastructure teams to define technical requirements, lead prototypes into production, and establish best practices for safety, scalability, and performance. The role also involves mentoring engineers, managing technical decisions, and contributing to long-term roadmap planning for robotics-enabled automation solutions.