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Bedrock Robotics is deploying autonomous systems on heavy construction equipment across the country. The company has raised $350M in two years and achieved the first fully autonomous excavator deployments in construction, with a team including veterans from Waymo, Segment, and Uber Freight.
As Fleet Engineering scales deployments nationwide, you will own the platform behind the machine lifecycle: the system of record, services, and applications that teams use to run a fleet growing to thousands of machines. These systems will also be used by external partners.
Key responsibilities:
- Own the fleet system of record: the data model and services for machines, hardware, worksites, deployments, and lifecycle management
- Build applications that technicians, dispatchers, and operations teams use daily to vet machines, schedule installs, track inventory, and maintain fleet health
- Build services that robots phone home to, delivering identity, credentials, calibrations, and configuration to machines in the field
- Move petabytes of sensor data from remote job sites across the country, powering ML and learning flywheel
- Spend time with end users—technicians and operators—in the office and field to understand workflows and translate them into durable software
- Design foundational APIs that other engineering teams and external partners build on, evolving them safely as the business scales
- Incorporate AI and agents into fleet operations, from automating development workflows to fleet triage
You'll work alongside construction veterans and world-class engineers solving physical-world problems that simulations cannot address. The role crosses disciplines: one week architecting sensor calibration tracking, the next making fault diagnostics readable on an operator's tablet. You own problems end-to-end, collaborating with field technicians, operators, and multidisciplinary engineers across hardware, ML, and robotics.
REQUIREMENTS:
- 5+ years building and shipping production software, owning systems from design through operation
- Strong backend and data-modeling skills: you have designed schemas and services that many other systems depend on
- Ability to build full-stack applications, including interfaces people actually want to use
- Product sense: you start from the user's problem and prioritize shipping the useful version over the elegant one
- Comfort with ambiguity: you can take a vague cross-functional problem, define it, and drive it to completion
- Clear communication with teams outside engineering (users may operate excavators, repair hardware in the field, or work directly with customers)
PREFERRED:
- Experience managing fleets of physical assets, IoT devices, or robots
- Experience with edge systems: intermittent connectivity, device provisioning, large data transfers
- Experience in operations-heavy domains such as manufacturing, logistics, supply chain, field service, or construction
- Experience running high-uptime services on AWS with strong observability
- Experience with Python, TypeScript, Rust, or Postgres
