Support Engineer

Job description

RIVR, part of Amazon is a robotics company pioneering Physical AI through real-world doorstep delivery. Founded in 2024 as an ETH Zurich spin-off, RIVR developed wheeled-legged robots designed to operate in complex, unstructured environments such as stairs, gates, doors, and uneven urban terrain. We believe that achieving general physical intelligence requires solving real customer problems in the real world, where robots can learn from rich operational data at scale. Following our acquisition by Amazon in March 2026, we are continuing this mission with greater reach and speed. By combining custom robot hardware, onboard autonomy, and cloud-based coordination, RIVR, part of Amazon is building the next generation of safe, reliable autonomous robots for last-mile delivery ### **Job Description** As we scale globally and integrate into Amazon's infrastructure, we are looking for a highly capable Support Engineer to help build, secure, and operate the technical foundation that powers our teams, labs, and operations. This is not a traditional helpdesk role. You will be the engineer behind the systems that enable hundreds of employees, robotics researchers, software engineers, and hardware teams to work efficiently and securely every day. From designing segmented lab networks and managing Linux infrastructure to automating workflows and supporting Amazon integration projects, you will work at the intersection of IT, infrastructure, security, and developer productivity. You will be responsible for ensuring that our offices, labs, devices, and internal systems scale reliably as we grow from a fast-moving robotics startup into part of one of the world's largest technology organizations. If you enjoy solving complex technical problems, automating everything possible, and building scalable infrastructure in a highly innovative environment, we'd love to hear from you. ### What you’ll be doing - Implement, maintain, and optimize IT infrastructure, with a strong focus on network architecture, Linux systems, audio/video, and end-user devices, ensuring maximum availability and performance - Configure and troubleshoot network infrastructure including switches, routers, firewalls, VLANs, and wireless systems - Design and maintain lab network segmentation, including isolated VLANs, dedicated lab subnets, and semi-air-gapped environments to support AI/ML development, hardware prototyping and testing workflows - Perform site audits on technical infrastructure of a temporary office and implement improvements for security and stability purposes - Manage employee onboarding from an IT perspective — account provisioning, hardware setup, system access, and orientation on internal tools - Device imaging, configuration, and lifecycle management for end-user hardware (laptops, workstations, peripherals) - Provide day-to-day IT support to on-site employees, troubleshooting hardware, software, and connectivity issues - Identify and drive programs to improve G&A operational effectiveness by collaborating with the AI/ML team to design, implement, and maintain productivity automations and tooling for internal workflows ### What you must have - Strong knowledge of Linux-based systems (administration, scripting, troubleshooting) - Good working knowledge of macOS and Windows operating systems - Solid networking experience (routing, switching, VLANs, firewalls, wireless) - Minimum 5+ years of technical support experience in an enterprise or lab environment - Proficiency in scripting and automation (Python, Bash, or similar) with a DevOps mindset — experience with CI/CD pipelines, infrastructure-as-code, and workflow automation - Strong analytical and problem-solving skills with a hands-on approach - Ability to work independently and prioritize in a fast-paced, evolving environment ### Get some bonus points - Experience with Ubiquiti networking equipment is a plus - Familiarity with AI/ML lab environments and air-gapped network configurations - Experience with Amazon internal systems (e.g., Midway, Conduit, CORP network, Isengard) is a significant advantage — internal transfer is not currently possible due to cost center constraints, but candidates with prior Amazon experience are highly preferred - Strong AWS experience (EC2, VPC, IAM, CloudFormation, Lambda, or similar) - required for infrastructure automation and cloud-native tooling