Staff Site Reliability Engineer — AI-Driven Reliability

EarnIn; Mountain View (CA); Hybrid; USD 252,000 - 308,000; Full time

Benefits offered by this job

Equity

Hybrid work model

Job summary

EarnIn seeks a Staff Site Reliability Engineer to drive AI-first reliability across critical services in a hybrid Mountain View setting. You will guide reliability strategy, mentor engineers, and lead incident response with AI-assisted workflows, aiming to reduce toil and improve production readiness.

You will shape observability, capacity planning, and resilience patterns while partnering with product engineering, security, and leadership to embed AI-driven reliability into teams' workflows.

Qualifications

• Lead reliability initiatives at scale with AI-assisted workflows.
• Define SLIs/SLOs and incident response standards across services.
• Mentor engineers and codify reusable reliability patterns.

Responsibilities

• Define and evolve reliability standards across critical services with AI-assisted analysis.
• Oversee incident lifecycle as Incident Commander and improve runbooks and postmortems.
• Reduce toil by automating repetitive investigations and improving on-call quality.
• Architect for resilience, capacity planning, and graceful degradation in AWS.
• Mentor teams and publish tooling to spread reliability knowledge.

Skills

Staff leadership

AI-first thinking

Incident response

Observability

Education

7+ years SRE/Infra

Tools

Datadog

CloudWatch

Kubernetes

Terraform

OpenTelemetry

Job description

EarnIn seeks a Staff Site Reliability Engineer to drive AI-first reliability across critical services in a hybrid Mountain View setting. You will guide reliability strategy, mentor engineers, and lead incident response with AI-assisted workflows, aiming to reduce toil and improve production readiness.

You will shape observability, capacity planning, and resilience patterns while partnering with product engineering, security, and leadership to embed AI-driven reliability into teams' workflows.