Software Engineer, Backend
Summary
Owns the backend that ingests, stores, and reports on telemetry, video, and sensor data from BurnBot's remotely operated prescribed-fire machines: building services and APIs, managing terabytes of field data in the cloud, and producing treatment reports for agency and utility customers. Stack includes Python/Go/Rust/TypeScript, AWS or GCP, and time-series/geospatial databases like PostGIS.
About BurnBot
Wildfire has stopped being a season. BurnBot builds the machines that get ahead of it — remotely operated systems that apply and contain prescribed fire, and platforms that clear heavy fuel on terrain that isn’t safe for crews.
Our fleet is at work today for PG&E, CAL FIRE, the U.S. Forest Service, Caltrans, fire districts, and tribal nations across California, Oregon, and Washington — treating land at up to 40x the pace of conventional methods. We’re roboticists, engineers, and career fire practitioners. Hardware we design in South San Francisco is in the dirt within weeks, and the people who designed it are usually standing next to it.
THE ROLE
Every machine in the field produces telemetry, video, lidar, logs, and a record of exactly what got treated — and our agency and utility customers need that record to be right, because it’s what they report on.
You’ll own the backend that carries all of it: ingest, storage, APIs, and the reporting that turns a day of machine work into something a land manager can act on.
WHAT YOU’LL OWN
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Services and APIs behind our operator tools, fleet management, and customer reporting
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Ingest at field scale: high-rate telemetry plus large video and sensor payloads, from machines on links that drop
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Storage and infrastructure — cloud, cost, and the retention decisions that come with terabytes of field data
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Treatment reporting: acres, coverage, and verification our customers can defend to their own stakeholders
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Reliability and observability. When a crew is on a burn unit, our systems being down is not an inconvenience
WHAT YOU’LL BRING
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7+ years building and operating backend systems in production (Python, Go, Rust, TypeScript, or similar)
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Distributed systems and data pipeline experience, especially with high-volume time-series data
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Cloud infrastructure (AWS or GCP) and infrastructure as code
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Solid API design instincts and real database depth, including time-series or geospatial (PostGIS) work
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Observability practice — you instrument first and guess second
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Pragmatism about intermittent connectivity. The machine is not always online, and the data still has to arrive
NICE TO HAVE
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Robotics, IoT, or connected-fleet data at scale
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Offline-first sync or store-and-forward architectures
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Geospatial data and mapping services
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Video or sensor-data pipelines
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Reporting for government or utility customers, and the compliance that comes with it
