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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 that includes veterans from Waymo, Segment, and Uber Freight.
As a Staff Site Reliability Engineer, you will take ownership of Bedrock's cloud infrastructure and be central to scaling the systems that power critical data pipelines for Machine Learning and Robotics engineering teams. This is a high-leverage role focused on production engineering, observability, and resilient distributed systems.
Key responsibilities:
- Design, build, and operate highly scalable, reliable systems used across all Bedrock engineering teams
- Take full ownership of Bedrock's cloud infrastructure (AWS, GCP, Azure), ensuring best-in-class security, performance, and cost efficiency
- Design, implement, and maintain the end-to-end observability stack, including monitoring, logging, and tracing
- Develop and implement best practices for system reliability, security, on-call rotation, and incident response
- Continuously identify and implement improvements to enhance system performance and optimize cloud resource consumption
You will work alongside construction veterans and world-class engineers to solve physical-world problems that simulations cannot address.
REQUIREMENTS:
- Deep passion for building and maintaining reliable, fault-tolerant distributed systems
- Strong proficiency in major cloud platforms (AWS, GCP, or Azure) and Infrastructure as Code tools like Terraform
- Proven experience with container technologies and orchestration platforms, particularly Kubernetes
- Hands-on experience with observability tools (e.g., Datadog, Prometheus, Splunk)
- Strong understanding of distributed systems, networking concepts, database technologies, and compute infrastructure
- Strong understanding and experience implementing security best practices in cloud environments
- Ability to work in a fast-paced, high-growth environment, deal effectively with ambiguity, and take decisive ownership of challenging problems
