Beacon Venture Capital

Cloud Infrastructure Engineer, IoT/Edge

Beacon Venture Capital

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

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Job Level

Mid-LevelSenior

Tech Stack

AWSCloudDockerIoTKubernetesLinuxPrometheusTerraform

About the role

  • About Beacon AI: We’re a fast-moving team of aviators, engineers, and operators on a mission to transform aviation with an AI platform that makes flying safer, more efficient, and more capable. Role Overview: Lead design, implementation, and optimization of cloud and edge infrastructure; ensure reliable, scalable, secure deployment of applications to connected devices in the field. Responsibilities: - Design, implement, and maintain infrastructure for secure cloud-to-edge deployments using AWS Greengrass and other edge platforms. - Build scalable provisioning, registration, and fleet management systems for Linux-based edge devices. - Own CI/CD pipelines for cloud infrastructure and field devices, including OTA updates, rollbacks, and monitoring. - Optimize infrastructure for cost, observability, and performance. - Develop monitoring tools and contribute to incident response for IoT and cloud systems. - Collaborate with embedded systems engineers to integrate edge applications with cloud services.

Requirements

  • Extensive Infrastructure Experience: 6–10+ years of experience in cloud infrastructure, DevOps, or Site Reliability Engineering roles, ideally with significant exposure to edge or IoT systems. Hands-on Technical Expertise: Strong experience with AWS services (Greengrass, IoT Core), containerized deployments (e.g., Docker), and Infrastructure as Code tools like AWS CDK, Terraform, or Kubernetes. Edge & Device Focus: Experience provisioning, securing, and deploying software to edge compute devices (Jetson, Raspberry Pi, etc.) in production environments. Secure Communication & System Design: Deep understanding of edge-to-cloud messaging protocols like MQTT and encrypted data exchange between devices and cloud systems. Ownership & Initiative: Thrives in fast-paced, ambiguous environments with a strong bias toward action. Collaborative Leadership: Effective at working across disciplines (hardware, embedded, software) and mentoring junior engineers to raise the technical bar.