Staff Site Reliability Engineer
New
E
EthosLife insurance technology
Remote USFull-TimeStaff
Salary156,000 - 275,000 USD per year
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Job Details
- Experience
- 10+ years of full-time software engineering experience in relevant roles (SRE, Infrastructure, Platform, DevOps, or Backend SWE)
- Required Skills
- AWSPostgreSQLPythonKubernetesTypeScriptGoCI/CDTerraformDistributed Systems
Requirements
- Have 10+ years of full-time software engineering experience in SRE, Infrastructure, Platform, DevOps, or Backend SWE roles.
- Have significant experience operating production systems at scale.
- Show a track record of leading complex, multi-team infrastructure or reliability initiatives from ambiguity to delivery.
- Demonstrate strong coding skills in Golang, Python, or TypeScript.
- Have deep, hands-on experience with AWS, Kubernetes, and Terraform.
- Understand distributed systems, PostgreSQL, CI/CD systems, and observability tooling such as DataDog.
- Have hands-on experience implementing SLIs/SLOs, leading incident response, and running post-mortems.
- Apply engineering best practices including design patterns, code reviews, and testing.
- Be able to write design documents, explain trade-offs, and build consensus across teams.
- Have judgment to balance reliability, velocity, and cost.
Responsibilities
- Set multi-quarter technical strategy for reliability, infrastructure, and platform tooling with SRE and engineering leadership.
- Lead the design of cross-cutting infrastructure systems and author or review technical specifications and architecture proposals.
- Advise product engineering teams on reliability practices and production readiness.
- Establish frameworks for defining, measuring, and monitoring SLIs, SLOs, and error budgets.
- Lead technical response to high-severity incidents and drive blameless post-mortems and recurrence-reducing follow-up work.
- Lead capacity planning, disaster recovery, failure-mode testing, and observability improvements.
- Design, build, and operate AWS infrastructure using Terraform, Kubernetes, and GitOps workflows including ArgoCD and Atlantis.
- Build governed AI gateways with model access controls, audit trails, and secure data connectors.
- Lead cloud cost optimization and develop metering, budgeting, and cost-aware routing for LLM usage.
- Build internal tools, CI/CD pipelines, and self-service platforms, and automate sources of engineering toil.
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