Ethos Life - Staff Site Reliability Engineer
Requirements
• Experience: 10+ years of full-time software engineering experience in relevant roles (SRE, Infrastructure, Platform, DevOps, or Backend SWE), including significant time operating production systems at scale. • Staff-Level Impact: A track record of leading complex, multi-team infrastructure or reliability initiatives from ambiguity to delivery, and of influencing technical direction beyond your immediate team. • Staff-Level Impact: • Software Engineering: Strong coding skills in Golang, Python, or TypeScript, and a commitment to engineering best practices: design patterns, code reviews, and testing. • Software Engineering: • Golang, Python, or TypeScript • Cloud & Platform Expertise: Deep, hands-on experience with AWS, Kubernetes, and Terraform. Experience building Kubernetes operators is a plus. • Cloud & Platform Expertise: • AWS, Kubernetes, and Terraform • Systems Knowledge: Strong understanding of distributed systems, PostgreSQL, CI/CD systems, and observability tooling such as DataDog. • Systems Knowledge: • Reliability Practice: Hands-on experience implementing SLIs/SLOs, leading incident response, and running effective post-mortems. • Reliability Practice: • Communication: Excellent written and verbal communication. You can write a clear design doc, explain trade-offs to executives, and build consensus across teams. • Communication: • Mindset: A strong desire to remove toil from systems, and the judgment to balance reliability, velocity, and cost. • Mindset: • Experience building or operating LLM toolchains, such as AI gateways, model routing (e.g., Bedrock, Anthropic), and governance frameworks, including PII scanning and audit trails for model interactions. • AI gateways, model routing (e.g., Bedrock, Anthropic), and governance frameworks • Demonstrated experience leading cloud cost optimization or building usage metering systems. • Experience in regulated industries (insurance, fintech, healthcare) or with compliance frameworks such as SOC 2. • Experience collaborating with globally distributed teams. • Languages: TypeScript, Golang, Python • Languages: • Infrastructure: AWS, Kubernetes, Terraform, ArgoCD, Atlantis • Infrastructure: • Observability & Tools: DataDog, GitHub Actions, PostgreSQL • Observability & Tools: • AI Platform: Anthropic, Bedrock, MCP • AI Platform: • #LI-Remote #LI-MK1 • #LI-Remote #LI-MK1 • The US national base salary range for this full-time position is $156,000 - $275,000. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. • Please note that the compensation details listed in US role postings reflect the base salary only and do not include applicable bonus, equity, or benefits. • You can find further details of our US benefits at https://www.ethoslife.com/careers/ • Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. At Ethos we are dedicated to building a diverse, inclusive and authentic workplace.
Responsibilities
• Technical Leadership & Strategy • Set Direction: Define and drive the multi-quarter technical strategy for reliability, infrastructure, and platform tooling, in partnership with SRE and engineering leadership and aligned with company OKRs. • Set Direction: • Architecture: Lead the design of complex, cross-cutting infrastructure systems. Author and review technical specifications and architecture proposals to ensure consistency, resilience, and long-term maintainability. • Architecture: • Influence Without Authority: Motivate product engineering teams to adopt reliability best practices, and act as a trusted advisor on production readiness when new services are designed and brought online. • Influence Without Authority: • Mentorship: Grow the technical skills of SREs across our US and Bangalore teams through design reviews, pairing, and code review, and help raise the hiring bar by participating in interviews. • Mentorship: • Reliability & Performance Engineering • Service Standards: Establish the framework for how teams define, measure, and act on SLIs, SLOs, and error budgets. Help teams instrument and monitor them. • Service Standards: • Incident Excellence: Serve as a senior technical leader during high-severity incidents. Drive a culture of rigorous, blameless post-mortems and ensure follow-up work actually reduces recurrence. • Incident Excellence: • Resilience: Lead capacity planning, disaster recovery, and failure-mode testing so our systems degrade gracefully and recover quickly. • Resilience: • Observability: Evolve our monitoring and alerting strategy so failures are detected before they impact customers and on-call is sustainable. • Observability: • Infrastructure & AI Platform Tooling • Scalable Systems: Design, build, and operate our AWS cloud infrastructure using Infrastructure as Code (Terraform), Kubernetes, and GitOps workflows (ArgoCD, Atlantis). • Scalable Systems: • AI Gateway & Governance: Architect and build governed gateways for AI model routing, including model access controls, audit trails, and secure data connectors (such as MCP) that prevent sensitive data exposure. • AI Gateway & Governance: • Security & Compliance: Ensure infrastructure, including AI prototyping environments, meets security and regulatory requirements through automated scanning, PII guardrails, and scoped data access. • Security & Compliance: • Efficiency & Cost Optimization • FinOps: Lead initiatives to optimize cloud spend across the organization, including right-sizing, spot instance utilization, and cost attribution. • FinOps: • AI Cost Management: Design metering and budgeting for LLM token usage, and build cost-aware routing so workloads use the most efficient model for the job. • AI Cost Management: • Visibility: Establish clear cost metrics and partner with engineering teams on architectures that are both performant and cost-effective. • Visibility: • Paved Roads: Build internal tools, CI/CD pipelines, and self-service platforms that make the reliable path the easy path for product engineering teams. • Paved Roads: • Toil Elimination: Identify systemic sources of toil across engineering and automate them away. • Toil Elimination:
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