DevOps Engineer

Evlo AI; Los Angeles (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Evlo AI is seeking a hands-on DevOps/SRE to own production infrastructure including Kubernetes on AWS, CI/CD, and observability tooling. You will work with backend engineers and SREs to improve reliability and reduce toil.

This role will involve debugging production issues, cost optimization, and automating repetitive tasks, while leading incident responses and designing scalable platforms for multi-team use.

Qualifications

• 3–6 years of experience in DevOps, SRE, or infrastructure engineering, with at least 2 years running production workloads in AWS or GCP
• Deep hands-on experience with Kubernetes - cluster operation, networking, RBAC, and debugging workloads in production
• Strong infrastructure-as-code skills with Terraform; comfortable managing multi-environment deployments with CI/CD automation
• Proficiency in at least one scripting or programming language: Python, Go, or Bash
• Experience with monitoring and alerting stacks (Prometheus/Grafana, Datadog, or similar) and a track record of improving reliability metrics (SLOs, MTTR, error budgets)
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
• Bonus: experience with service mesh (Istio/Linkerd), chaos engineering, multi-region architectures, or AWS certifications (Solutions Architect, DevOps Professional)

Responsibilities

• Build and maintain Kubernetes-based infrastructure on AWS (EKS, Terraform, Helm), owning provisioning through production operation
• Design and manage CI/CD pipelines in GitHub Actions or GitLab CI, including canary deployments, automated rollback, and artifact promotion
• Implement observability tooling with Prometheus, Grafana, and OpenTelemetry, defining SLOs and actionable alerting across services
• Automate infrastructure as code with Terraform and Ansible, enforcing security and compliance guardrails across cloud accounts
• Lead incident response and blameless postmortems; drive root-cause fixes and build runbooks for common failure modes
• Optimize cloud spend and system performance - right-size compute, tune autoscaling, and eliminate single points of failure
• Partner with engineering teams on capacity planning, load testing, and platform reliability improvements

Skills

DevOps

SRE

Automation

Capacity planning

Incident response

Education

Bachelor's degree in Computer Science, Engineering, or equivalent

Tools

Terraform

Kubernetes

GitHub Actions

GitLab CI

Prometheus/Grafana

OpenTelemetry

Job description

About The Role

The role owns the infrastructure that keeps production systems online at scale - Kubernetes clusters, CI/CD pipelines, cloud environments, and the observability tooling that surfaces problems before customers notice.

You will work closely with backend engineers and SREs on reliability targets, incident response, and platform improvements. This is a hands-on role: expect to debug production issues, cut infrastructure costs, and automate yourself out of repetitive work.

Key Responsibilities

• Build and maintain Kubernetes-based infrastructure on AWS (EKS, Terraform, Helm), owning provisioning through production operation
• Design and manage CI/CD pipelines in GitHub Actions or GitLab CI, including canary deployments, automated rollback, and artifact promotion
• Implement observability tooling with Prometheus, Grafana, and OpenTelemetry, defining SLOs and actionable alerting across services
• Automate infrastructure as code with Terraform and Ansible, enforcing security and compliance guardrails across cloud accounts
• Lead incident response and blameless postmortems; drive root-cause fixes and build runbooks for common failure modes
• Optimize cloud spend and system performance - right-size compute, tune autoscaling, and eliminate single points of failure
• Partner with engineering teams on capacity planning, load testing, and platform reliability improvements

What We Are Looking For

• 3–6 years of experience in DevOps, SRE, or infrastructure engineering, with at least 2 years running production workloads in AWS or GCP
• Deep hands-on experience with Kubernetes - cluster operation, networking, RBAC, and debugging workloads in production
• Strong infrastructure-as-code skills with Terraform; comfortable managing multi-environment deployments with CI/CD automation
• Proficiency in at least one scripting or programming language: Python, Go, or Bash
• Experience with monitoring and alerting stacks (Prometheus/Grafana, Datadog, or similar) and a track record of improving reliability metrics (SLOs, MTTR, error budgets)
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
• Bonus: experience with service mesh (Istio/Linkerd), chaos engineering, multi-region architectures, or AWS certifications (Solutions Architect, DevOps Professional)