Staff Site Reliability Engineer

Description

The company is a life insurance technology business listed on Nasdaq. Its three-sided platform serves consumers, agents, and carriers, and it sells instant online life insurance that needs no medical exam, only a few health questions.

This is a Staff Site Reliability Engineer role leading the technical side of the US SRE group. You will shape how production systems are built, run, and scaled, covering core AWS and Kubernetes infrastructure and the internal platforms and toolchains behind the company's AI work.

It is a senior, hands-on individual contributor role with scope across the whole engineering organization. You will design and build critical infrastructure, drive cross-team projects from start to finish, and submit pull requests to product teams' codebases when needed. You will work with SRE leadership in the US and Bangalore on the roadmap and serve as the go-to expert on reliability, scalability, security, and cost.

Responsibilities

• Set the multi-quarter technical direction for reliability, infrastructure, and platform tooling, working with SRE and engineering leaders and tied to company OKRs.
• Lead the design of complex, cross-cutting infrastructure. Write and review technical specs and architecture proposals that keep systems consistent, resilient, and easy to maintain.
• Persuade product engineering teams to adopt reliability practices without formal authority, and advise them on production readiness when new services are built and launched.
• Build the skills of SREs in the US and Bangalore through design reviews, pairing, and code review, and help raise the hiring bar by interviewing candidates.
• Create the framework teams use to define, measure, and act on SLIs, SLOs, and error budgets, and help them instrument and monitor these.
• Lead high-severity incidents as the senior technical voice. Promote blameless post-mortems and make sure follow-up work reduces repeat incidents.
• Lead capacity planning, disaster recovery, and failure-mode testing so systems degrade gracefully and recover fast.
• Improve monitoring and alerting so problems are caught before customers feel them and on-call stays sustainable.
• Design, build, and run AWS infrastructure with Infrastructure as Code in Terraform, Kubernetes, and GitOps workflows using ArgoCD and Atlantis.
• Architect and build governed gateways for AI model routing, with model access controls, audit trails, and secure data connectors such as MCP that stop sensitive data from leaking.
• Make sure infrastructure, including AI prototyping environments, meets security and regulatory requirements through automated scanning, PII guardrails, and tightly scoped data access.
• Lead programs that cut cloud spend across the organization, including right-sizing, use of spot instances, and cost attribution.
• Design metering and budgets for LLM token use, and build cost-aware routing that sends each workload to the most efficient model for it.
• Set up clear cost metrics and work with engineering teams on architectures that are both fast and affordable.
• Build internal tools, CI/CD pipelines, and self-service platforms that make the reliable approach the easiest one for product teams.
• Find the systemic sources of toil across engineering and automate them.

Requirements

• 10+ years of full-time software engineering in roles such as SRE, infrastructure, platform, DevOps, or backend, including substantial time running production systems at scale.
• A record of leading complex, multi-team infrastructure or reliability projects from unclear starting point to delivery, and of shaping technical direction beyond your own team.
• Strong coding in Golang, Python, or TypeScript, with commitment to design patterns, code review, and testing.
• Deep hands-on experience with AWS, Kubernetes, and Terraform. Experience building Kubernetes operators is a plus.
• Solid grasp of distributed systems, PostgreSQL, CI/CD systems, and observability tools such as DataDog.
• Hands-on experience setting SLIs and SLOs, leading incident response, and running effective post-mortems.
• Excellent written and spoken communication. You can write a clear design doc, explain trade-offs to executives, and get agreement across teams.
• A strong drive to remove toil, and the judgment to balance reliability, speed of delivery, and cost.
• Experience building or running LLM toolchains, such as AI gateways, model routing with tools like Bedrock or Anthropic, and governance frameworks including PII scanning and audit trails for model interactions.
• Proven experience leading cloud cost reduction or building usage metering systems.
• Experience in regulated industries such as insurance, fintech, or healthcare, or with compliance frameworks such as SOC 2.
• Experience working with globally distributed teams.

Conditions

Full-time, remote role based in the US.

The US national base salary range is $156,000 - $275,000. This covers base salary only and excludes bonus, equity, and benefits.

The range is the minimum and maximum target for new hires across all US locations. Final pay depends on work location, skills, experience, and relevant education or training.

Details of US benefits are on the company careers page.

We are an equal opportunity employer and consider qualified applicants with arrest or conviction records under the SF Fair Chance Ordinance.