Site Reliability Engineer

Evlo AI; Seattle (WA); On-site; USD 120,000 - 180,000; Full time

Job summary

Evlo AI is seeking a Site Reliability Engineer to keep large-scale distributed systems fast, available, and observable. You will own reliability for production services, define SLOs/SLIs, and drive decisions based on reliability data.

You will build observability tooling with Prometheus, Grafana, and OpenTelemetry, design alerting to reduce noise, and participate in on-call rotations across multi-region cloud environments (AWS/GCP).

Qualifications

• 3–7 years of experience in SRE, DevOps, or infrastructure engineering, including production on-call experience.
• Strong programming skills in Go, Python, or Bash for building automation, tooling, and internal platforms.
• Deep hands-on experience with Kubernetes in production — deployment, debugging, RBAC, networking, and helm-based packaging.
• Experience with infrastructure-as-code (Terraform) and CI/CD systems (GitHub Actions, GitLab CI, or Jenkins).
• Solid grasp of distributed systems fundamentals: load balancing, caching, consistency, and failure modes at scale.
• BS in Computer Science or equivalent practical experience.
• Bonus: Experience with service mesh (Istio/Linkerd), chaos engineering tooling (Gremlin, Litmus), cloud cost optimization, or contributions to open-source infrastructure projects

Responsibilities

• Own reliability for production services end-to-end: define SLOs/SLIs, build error budgets, and drive engineering decisions based on reliability data.
• Build and maintain observability tooling with Prometheus, Grafana, and OpenTelemetry; design alerting that pages on real problems, not noise.
• Lead incident response for high-severity outages — run blameless postmortems, drive root-cause analysis, and ship preventive fixes.
• Automate infrastructure provisioning and configuration using Terraform, Ansible, and GitOps workflows (ArgoCD) across multi-region cloud environments (AWS/GCP).
• Harden and scale Kubernetes-based platforms: capacity planning, autoscaling policies, node tuning, and cluster upgrade rollouts.
• Reduce toil through automation — build self-service tooling in Go or Python so developers can deploy, debug, and scale services without ticket handoffs.
• Participate in an on-call rotation and contribute to runbooks, chaos engineering exercises, and disaster recovery testing

Skills

Go

Python

Bash

Kubernetes

GitOps

CI/CD

Distributed systems

On-call

Education

BS in Computer Science or equivalent practical experience

Tools

Terraform

Ansible

ArgoCD

GitHub Actions

GitLab CI

Jenkins

Job description

About The Role

The role keeps large-scale distributed systems fast, available, and observable. This team owns the reliability of production infrastructure — Kubernetes clusters, service meshes, CI/CD pipelines, and the monitoring stack — that serves millions of requests per day.

SREs here blend software engineering and systems operations: writing automation that eliminates toil, setting SLOs with product teams, and leading incident response when things break. The work directly determines whether customers experience a fast, dependable product.

Key Responsibilities

• Own reliability for production services end-to-end: define SLOs/SLIs, build error budgets, and drive engineering decisions based on reliability data
• Build and maintain observability tooling with Prometheus, Grafana, and OpenTelemetry; design alerting that pages on real problems, not noise
• Lead incident response for high-severity outages — run blameless postmortems, drive root-cause analysis, and ship preventive fixes
• Automate infrastructure provisioning and configuration using Terraform, Ansible, and GitOps workflows (ArgoCD) across multi-region cloud environments (AWS/GCP)
• Harden and scale Kubernetes-based platforms: capacity planning, autoscaling policies, node tuning, and cluster upgrade rollouts
• Reduce toil through automation — build self-service tooling in Go or Python so developers can deploy, debug, and scale services without ticket handoffs
• Participate in an on-call rotation and contribute to runbooks, chaos engineering exercises, and disaster recovery testing

What We Are Looking For

• 3–7 years of experience in SRE, DevOps, or infrastructure engineering, including production on-call experience
• Strong programming skills in Go, Python, or Bash for building automation, tooling, and internal platforms
• Deep hands-on experience with Kubernetes in production — deployment, debugging, RBAC, networking, and helm-based packaging
• Experience with infrastructure-as-code (Terraform) and CI/CD systems (GitHub Actions, GitLab CI, or Jenkins)
• Solid grasp of distributed systems fundamentals: load balancing, caching, consistency, and failure modes at scale
• BS in Computer Science or equivalent practical experience
• Bonus: Experience with service mesh (Istio/Linkerd), chaos engineering tooling (Gremlin, Litmus), cloud cost optimization, or contributions to open-source infrastructure projects