Staff Site Reliability Engineer, Cloud

Bedrock Robotics

. Design, build, and operate highly scalable, reliable systems used by all Bedrock engineering teams .

Posted 10/16/2026full-timeUnited StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and maintaining scalable cloud infrastructure across AWS, GCP, and Azure, with a strong focus on security, performance, and observability. Proven ability to implement production engineering best practices and optimize resource consumption for distributed systems.

Highest-signal resume keywords

AWS Cloud InfrastructureGCP Cloud InfrastructureAzure Cloud InfrastructureInfrastructure As Code (Terraform)Container Technologies (Kubernetes)

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Distributed SystemsCloud Security Best PracticesObservability Tools (Datadog, Prometheus, Splunk)Networking ConceptsDatabase Technologies

Soft Skills

Decisive OwnershipAdaptability in Fast-Paced Environments

Industry Keywords

Production Engineering Best PracticesIncident ResponseSystem ReliabilityFault-Tolerant SystemsData Pipelines

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud PlatformKubernetesPrometheusSplunkTerraform

About the role

Key responsibilities & impact

Design, build, and operate highly scalable, reliable systems used by all Bedrock engineering teams
Take full ownership of Bedrock’s AWS, GCP, and Azure cloud infrastructure
Ensure best-in-class cloud security, performance, and cost efficiency
Design, implement, and maintain the end-to-end observability stack, including monitoring, logging, and tracing
Develop and implement production engineering best practices for system reliability, security, on-call rotation, and incident response
Identify and implement improvements to enhance system performance and optimize cloud resource consumption
Scale the infrastructure powering critical data pipelines for Machine Learning and Robotics engineering teams

Requirements

What you’ll need

Passion for building and maintaining reliable, fault-tolerant distributed systems
Strong proficiency in major cloud platforms such as AWS, GCP, or Azure
Proficiency with Infrastructure as Code tools such as Terraform
Proven experience with container technologies and orchestration platforms, particularly Kubernetes
Hands-on experience with observability tools such as Datadog, Prometheus, or 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
Legally authorized to work in the United States
Able to commute to the office 2–3 days a week

Benefits

Comp & perks

Equal Opportunity Employer commitment
Reasonable accommodations during the hiring process