What are the responsibilities and job description for the Site Reliability Engineer position at Evlo AI?
About The Role
The role focuses on keeping large-scale production infrastructure reliable: Kubernetes clusters, distributed services, and the observability stack that keeps engineers ahead of incidents instead of reacting to them.
The SRE works across infrastructure and application teams to set SLOs, automate away toil, and make deployments boring — building the tooling and practices that let a fast-moving engineering organization ship safely at scale.
Key Responsibilities
The role focuses on keeping large-scale production infrastructure reliable: Kubernetes clusters, distributed services, and the observability stack that keeps engineers ahead of incidents instead of reacting to them.
The SRE works across infrastructure and application teams to set SLOs, automate away toil, and make deployments boring — building the tooling and practices that let a fast-moving engineering organization ship safely at scale.
Key Responsibilities
- Own the reliability of production Kubernetes environments (EKS/GKE), including capacity planning, autoscaling policies, and cluster upgrades with zero downtime
- Define and enforce SLOs, SLIs, and error budgets; build dashboards and alerts in Prometheus, Grafana, and Datadog that page on symptoms, not causes
- Lead incident response for production outages — triage, mitigation, blameless postmortems, and tracking remediation to closure
- Build and maintain infrastructure-as-code using Terraform and Helm across multi-region cloud environments (AWS primary)
- Improve CI/CD pipelines (GitHub Actions, ArgoCD) to enable progressive delivery with canary deployments and automated rollback
- Instrument services for observability — structured logging, distributed tracing (OpenTelemetry), and RED/USE metrics — in partnership with application teams
- Identify and eliminate toil through automation in Python or Go, targeting measurable reductions in manual operational work each quarter
- 3–7 years of experience in SRE, DevOps, or production infrastructure roles at companies operating services at meaningful scale
- Deep hands-on expertise with Kubernetes in production, including debugging workloads, managing operators, and tuning resource limits
- Strong infrastructure-as-code skills with Terraform; experience managing state at scale across teams and environments
- Production experience with at least one major cloud provider (AWS preferred) — networking, IAM, autoscaling, and cost awareness
- Proficiency in monitoring and observability tooling: Prometheus, Grafana, Datadog, or equivalent, including writing reliable alert logic
- Scripting or programming ability in Python, Go, or Bash sufficient to build and maintain automation tooling
- Bonus: Experience with service meshes (Istio/Linkerd), chaos engineering practices, multi-region failover design, or a BS/MS in Computer Science or related field