Staff Software Engineer - Streaming Infrastructure

Skills this role screens for

About the role

Skydio is the leading US drone company and the world leader in autonomous flight, the key technology for the future of drones and aerial mobility. The Skydio team combines deep expertise in artificial intelligence, best-in-class hardware and software product development, operational excellence, and customer obsession to empower a broader, more diverse audience of drone users, from utility inspectors https://www.skydio.com/solutions/energy-and-utilities to first responders https://www.skydio.com/solutions/public-safety, soldiers in battlefield scenarios https://www.skydio.com/solutions/national-security/tactical-isr, and beyond https://www.skydio.com/solutions.

The company

About the team

The Streaming team builds and operates the systems that move live video, telemetry, and control data between Skydio drones and our cloud platform. These systems support customers and internal teams across growing fleets, including devices operating over limited or unreliable networks. We work closely with device, networking, cloud infrastructure, security, and product teams to keep real-time communication reliable and responsive when it matters most.

The work

About the role

As a Staff Infrastructure Engineer on the Streaming team, you will shape the cloud infrastructure and operational foundations behind Skydio’s real-time streaming platform. You will work across Kubernetes, networking, deployment systems, and production services to improve reliability, performance, security, and efficiency.

This is a hybrid software and infrastructure role with the freedom to work across the stack, including making changes to application code to address underlying problems. You will define technical direction and lead cross-team initiatives that help our streaming platform scale with customer demand. Our backend services are primarily written in Go, with some Python and C++.

The work

How you will make an impact

• Design and evolve Kubernetes infrastructure for real-time services, driving capacity planning and compute and bandwidth efficiency as concurrent streaming demand grows.
• Improve deployment, scaling, and recovery workflows to minimize disruption to active streams.
• Establish service-level objectives and observability for stream availability, connection success, and latency; investigate failures across application code, Linux networking, and cloud infrastructure to prevent recurrence.
• Partner with device, networking, and product engineers to diagnose failures across the device-to-cloud path and enable new real-time capabilities.
• Work with security engineers to strengthen the practices and controls that protect customer data, drones, and streaming services.

Also

What makes you a good fit

• 8+ years in SRE, platform engineering, DevOps, or an equivalent infrastructure role, with demonstrated ability to define technical direction, lead cross-team initiatives, and translate business objectives into a technical roadmap.
• Strong experience operating and automating production Kubernetes clusters, with familiarity with AWS and continuous deployment systems, including safe rollout and rollback strategies.
• Experience operating distributed systems with long-lived connections, latency-sensitive traffic, or demanding availability requirements, and comfort fixing underlying issues in application code; Go preferred.
• Strong understanding of cloud networking, security, storage, and resilient application topologies, with experience diagnosing connectivity and performance issues across application, container, and cloud networking layers.
• Experience building observability and using production metrics, logs, traces, and profiling to investigate failures.

Nice to have

Bonus points

• Experience operating real-time video, communications, or device connectivity platforms, including drones or highly automated physical hardware.
• Familiarity with WebRTC, RTP/RTCP, ICE/STUN/TURN, or platforms such as LiveKit.
• Experience troubleshooting connectivity and performance issues in real