Site Reliability Engineer

Evlo AI; San Diego (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Evlo AI is seeking an experienced Site Reliability Engineer to own the reliability of production infrastructure, including Kubernetes clusters, distributed services, and the observability stack. You will work at the intersection of infrastructure engineering and incident response, automating toil, defining meaningful SLOs, and handling on-call duties in high-pressure situations.

You will design and operate containerized infrastructure on Kubernetes, implement IaC with Terraform and Helm, and

Qualifications

• 3–7 years of experience in SRE, DevOps, or infrastructure engineering.
• Hands-on Kubernetes production experience.
• Experience with cloud platforms (AWS, GCP, or Azure).
• Proficiency in scripting languages (Go, Python, or Bash).
• Strong observability and incident response skills.

Responsibilities

• Design, build, and operate containerized infrastructure on Kubernetes (EKS/GKE).
• Build infrastructure-as-code with Terraform and Helm; CI/CD with GitHub Actions or GitLab CI.
• Define and enforce SLOs/SLIs; build dashboards with Prometheus, Grafana, and Datadog.
• Lead incident response for production outages with blameless postmortems.
• Automate toil via runbooks, self-healing infra, and capacity planning scripts.
• Harden production systems with chaos testing and disaster recovery drills.
• Collaborate with application engineers on observability, load testing, and rollback paths.

Skills

Kubernetes production experience

Terraform

Cloud platforms (AWS/GCP/Azure)

Prometheus/Grafana/Datadog

Go/Python/Bash

Distributed systems fundamentals

On-call ownership

Chaos engineering tools (Litmus/Greml）

Tools

Terraform

Helm

GitHub Actions

GitLab CI

Prometheus

Grafana

Datadog

OpenTelemetry

Job description

About The Role

The role owns the reliability of production infrastructure serving millions of requests per day - Kubernetes clusters, distributed services, and the observability stack that keeps them honest.

About The Role

The role owns the reliability of production infrastructure serving millions of requests per day - Kubernetes clusters, distributed services, and the observability stack that keeps them honest.

You will sit at the intersection of infrastructure engineering and incident response: automating away toil, designing SLOs that actually mean something, and being the person the on-call rotation trusts when things break at 3am.

Key Responsibilities

• Design, build, and operate containerized infrastructure on Kubernetes (EKS/GKE), including cluster upgrades, autoscaling policies, and multi-environment rollout strategies


• Build and maintain infrastructure-as-code using Terraform and Helm, with CI/CD pipelines in GitHub Actions or GitLab CI for infrastructure changes


• Define and enforce SLOs/SLIs with error budgets; build dashboards and alerts in Prometheus, Grafana, and Datadog that page on real problems, not noise


• Lead incident response for production outages - triage, mitigation, root cause analysis, and blameless postmortems with actionable follow-through


• Automate away recurring operational toil: runbook automation, self-healing infrastructure, and capacity planning scripts


• Harden production systems for reliability and security - chaos engineering experiments, disaster recovery drills, and failover testing


• Partner with application engineers on service design reviews, ensuring new services ship with proper observability, load testing, and rollback paths

What We Are Looking For

• 3-7 years of experience in SRE, DevOps, or infrastructure engineering, including significant on-call ownership of production systems


• Deep hands-on expertise with Kubernetes in production - operating clusters, debugging workloads, and tuning resource limits and autoscaling behavior


• Strong infrastructure-as-code skills with Terraform (or equivalent) and experience managing cloud infrastructure on AWS, GCP, or Azure


• Production experience with observability tooling: Prometheus/Grafana, Datadog, or OpenTelemetry, including writing PromQL/queries from scratch


• Proficiency in at least one systems language: Go, Python, or Bash, with a track record of building internal tooling


• Solid grasp of distributed systems fundamentals: load balancing, caching, DNS, TLS, queuing, and failure modes at scale


• Bonus: experience with chaos engineering tools (Litmus, Gremlin), service mesh (Istio/Linkerd), cost optimization (FinOps), or running multi-region active-active architectures