Robotics System Integration Engineer

We're looking for an engineer who thrives on building the infrastructure that makes robotic systems reliable, observable, and scalable. You'll own the systems that keep field-deployed hardware running — deployment automation, health monitoring, and the tooling that gives us real-time visibility into every site. You'll also be the technical bridge between hardware, firmware, and software, making sure integration is clean from prototype to production. Strong instincts for diagnostics, observability, and debugging distributed systems are the core of the job.

WHAT YOU'LL DO

• Act as a technical bridge between hardware, firmware, and software teams, ensuring tight integration, clear ownership, and smooth handoffs from prototype to production.
• Build and maintain Docker-based deployment infrastructure, including container orchestration, logging, and automated updates across field-deployed edge devices.
• Design and implement health monitoring and observability tooling — thermal monitoring, network latency tracking, uptime alerting — so the team has real-time visibility into every deployed system.
• Stand up hardware-in-the-loop testing to catch integration issues before hardware reaches customer sites.
• Debug and resolve issues across the full stack, from hardware interfaces and sensor drivers to network communication and cloud connectivity.
• Optimize networking across edge devices, including data transfer between multiple LiDAR and camera streams.
• Travel occasionally to hangar sites to observe deployments, troubleshoot on-site, and bring field learnings back into the infrastructure.

REQUIREMENTS

• 3-5 years of experience in robotics, perception systems, or sensor integration.
• Strong proficiency in Python and C++.
• Experience with ROS2 in production environments.
• Hands-on experience with Docker in deployment contexts (containerization, logging, orchestration).
• Proven experience working on hardware integration or complex networked industrial equipment.
• Bachelor's or Master's (preferred) degree in Computer Science or Engineering, Robotics, Mechanical Engineering, Electrical Engineering, or related fields.

PREFERRED QUALIFICATIONS

• Experience building deployment and provisioning systems at scale.
• Background in aviation or aerospace environments.
• Experience with cloud infrastructure and edge-cloud communication (AWS, Temporal, Kubernetes).
• Practical understanding of network fundamentals (DNS, DHCP, TCP/IP, routing, switching, MQTT, DDS).
• Familiarity with monitoring and observability tools (Grafana, Prometheus, or similar).