Site Reliability Engineer

Evlo AI; Washington (District of Columbia); On-site; USD 140,000 - 180,000; Full time

Job summary

Evlo AI is seeking a Senior SRE/DevOps engineer to own the reliability of large-scale distributed production systems. You will design SLOs, manage incident response, and drive automation that reduces toil across AWS/GCP environments.

You will work with platform teams to harden infrastructure, implement observability pipelines with Prometheus, Grafana, and OpenTelemetry, and lead capacity planning for petabyte-scale traffic.

Qualifications

• 3–8 years of experience in SRE, DevOps, or infrastructure engineering, including on-call ownership of production systems serving significant traffic.
• Deep hands-on expertise with Kubernetes in production - cluster operations, Helm, autoscaling policies, and debugging workloads under pressure.
• Strong infrastructure-as-code skills with Terraform (or equivalent) and proficiency in at least one of Go, Python, or Bash for automation.
• Production experience with major cloud providers (AWS, GCP, or Azure), including networking, IAM, and cost awareness.
• Solid grasp of distributed systems fundamentals: consistency models, failure domains, backpressure, and graceful degradation.
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
• Bonus: experience with service mesh (Istio/Linkerd), GitOps tooling, chaos engineering tooling, or contributions to open-source infra projects

Responsibilities

• Design, implement, and maintain SLOs, SLIs, and error budgets for core services, and drive reliability reviews with engineering teams when budgets are at risk
• Build and maintain infrastructure as code using Terraform and Kubernetes (EKS/GKE), managing multi-environment deployments across AWS or GCP
• Lead incident response for production outages - triage, mitigation, postmortems, and driving remediation items to completion
• Develop observability pipelines using Prometheus, Grafana, and OpenTelemetry, with actionable alerting that pages humans only when it should
• Automate away recurring toil: runbook automation, self-healing infrastructure, and CI/CD pipeline reliability (GitHub Actions, ArgoCD)
• Perform capacity planning and performance tuning for stateful services - databases, message queues, caching layers - at petabyte-scale traffic
• Contribute to chaos engineering and load testing programs that surface failure modes before production traffic does

Skills

Kubernetes production

Terraform

Go

Python

Bash

Cloud platforms

On-call production support

Chaos engineering tools

Education

Bachelor's degree in CS/Engineering

Tools

Helm

Prometheus

Grafana

OpenTelemetry

Job description

About The Role

The role owns the reliability of large-scale, distributed production systems - SLOs, incident response, capacity planning, and the automation that keeps engineers from being paged for things a script should handle.

About The Role

The role owns the reliability of large-scale, distributed production systems - SLOs, incident response, capacity planning, and the automation that keeps engineers from being paged for things a script should handle.

You will work directly with platform engineers and service teams to reduce toil, harden infrastructure, and treat reliability as a software problem: measurable, testable, and continuously improving.

Key Responsibilities

• Design, implement, and maintain SLOs, SLIs, and error budgets for core services, and drive reliability reviews with engineering teams when budgets are at risk
• Build and maintain infrastructure as code using Terraform and Kubernetes (EKS/GKE), managing multi-environment deployments across AWS or GCP
• Lead incident response for production outages - triage, mitigation, postmortems, and driving remediation items to completion
• Develop observability pipelines using Prometheus, Grafana, and OpenTelemetry, with actionable alerting that pages humans only when it should
• Automate away recurring toil: runbook automation, self-healing infrastructure, and CI/CD pipeline reliability (GitHub Actions, ArgoCD)
• Perform capacity planning and performance tuning for stateful services - databases, message queues, caching layers - at petabyte-scale traffic
• Contribute to chaos engineering and load testing programs that surface failure modes before production traffic does

What We Are Looking For

• 3–8 years of experience in SRE, DevOps, or infrastructure engineering, including on-call ownership of production systems serving significant traffic
• Deep hands-on expertise with Kubernetes in production - cluster operations, Helm, autoscaling policies, and debugging workloads under pressure
• Strong infrastructure-as-code skills with Terraform (or equivalent) and proficiency in at least one of Go, Python, or Bash for automation
• Production experience with major cloud providers (AWS, GCP, or Azure), including networking, IAM, and cost awareness
• Solid grasp of distributed systems fundamentals: consistency models, failure domains, backpressure, and graceful degradation
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
• Bonus: experience with service mesh (Istio/Linkerd), GitOps workflows, chaos engineering tooling (Gremlin, LitmusChaos), or contributions to open-source infrastructure projects