Software Engineer, Fleet Platform
Engineer on the Fleet Platform team building the system of record, backend services, and internal/partner-facing apps that provision, monitor, calibrate, and service Bedrock's autonomous construction equipment fleet. Full-stack work spanning data modeling, APIs, and petabyte-scale sensor data ingestion, with preference for Python, TypeScript, Rust, Postgres, and AWS.
- Compensation
- Not disclosed
- Location
- New York, NY
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Software engineering
- Posted
Skills
Must have
- 5+ years building and shipping production software, owning systems from design through operation
- Strong backend and data-modeling skills: 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: start from the user's problem and ship the useful version over the elegant one
- Comfort with ambiguity: take a vague cross-functional problem, define it, and drive it to done
- Clear communication with teams outside engineering
Nice to have
- 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
Full description
Join the team bringing autonomy to the built world
At Bedrock, we're moving AI out of the lab and onto real job sites. Our team includes veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. We retrofit the heavy equipment contractors already own, starting with excavators, so experienced crews can safely take on more projects and deliver more of the critical infrastructure our society needs.
In August 2026, Bedrock-equipped excavators began doing fully autonomous, paid work on live commercial job sites. We've more than doubled our customer base since 2025, and our machines now work with contractors across the South, Midwest, and Mid-Atlantic
In October 2026, we raised a $600M Series C co-led by CapitalG and Emergence Capital, bringing our total funding to nearly $1B. We're using it to put more autonomous machines to work, build the field and operations teams behind every deployment, and expand into new machine types and job-site tasks.
This is where algorithms meet steel-toed boots. You'll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to do meaningful work on hard problems, we'd love to have you join us.
About the Role
As Bedrock scales deployments nationwide, every machine we bring autonomy to has to be vetted, provisioned, calibrated, deployed, monitored, updated and serviced. Fleet Engineering builds the platform behind that lifecycle: the system of record, services and applications that teams across Bedrock use to run a fleet growing to thousands of machines. Many of these systems will be used by external partners as well.
The work crosses disciplines. One week you're architecting how we track sensor calibrations across every machine. The next, you're making a fault on an operator's tablet readable at a glance. You'll own problems end to end, working closely with technicians and operators in the field as well as multidisciplinary engineers across hardware, ML and robotics.
Also, you get to drive 100,000 lb excavators.
What You'll Do
- Own the fleet system of record: the data model and services for machines, their hardware, worksites and deployments, and how each moves through its lifecycle
- Build the applications that technicians, dispatchers and operations teams use every day to vet machines, schedule installs, track inventory and keep the fleet healthy
- Build the services every robot phones home to: delivering identity, credentials, calibrations and configuration to machines in the field, and always knowing what's running where
- Move petabytes of sensor data off remote job sites across the country, bringing home the real-world data that powers our ML and learning flywheel