Site Reliability Engineer

Evlo AI; New York (NY); On-site; USD 140,000 - 200,000; Full time

Job summary

Evlo AI is seeking an experienced SRE to own the reliability of production systems, including Kubernetes clusters, distributed services, and CI/CD pipelines. You will join a platform team responsible for observability, capacity planning, and automation across a multi-region cloud environment.

This is hands-on infrastructure engineering — code, not tickets. You will lead incident response, drive troubleshooting, and implement durable fixes while building tooling in Go or Python to reduce toil and

Qualifications

• 3–6 years of experience in SRE, DevOps, or infrastructure engineering, with on‑call ownership of large‑scale production systems.
• Hands-on Kubernetes production experience across regions, including troubleshooting stateful workloads and networking.
• Strong programming skills in Go or Python for building tooling and automation.
• Production cloud experience with AWS, GCP, or Azure including networking, IAM, and cost management.
• Solid grounding in Linux, TCP/IP, load balancing, and distributed systems failure modes.
• Track record of leading incident response and writing high‑quality postmortems that drive systemic fixes.
• Bonus: experience with service meshes (Istio/Linkerd), chaos engineering tools, database ops.

Responsibilities

• Build, operate, and scale production Kubernetes clusters (EKS/GKE) across multiple regions, including node autoscaling and upgrades.
• Design and maintain observability infrastructure with Prometheus, Grafana, and OpenTelemetry including SLO-based alerting.
• Lead incident response for production outages, drive triage, coordinate communication, and land follow-up fixes.
• Automate infrastructure as code with Terraform and CI/CD pipelines in GitHub Actions or ArgoCD, enforcing GitOps workflows.
• Define and track reliability targets (SLOs, error budgets) with product teams and drive capacity planning for growing services.
• Harden production systems with chaos engineering, disaster recovery drills, load testing, and runbook automation.
• Write tooling in Go or Python to reduce toil and build self-service deployment tools and automated health checks.

Skills

Go

Python

On-call ownership

Incident response

SRE/DevOps mindset

Automation mindset

Tools

Kubernetes (EKS/GKE)

Prometheus

Grafana

OpenTelemetry

Terraform

GitHub Actions

ArgoCD

AWS

GCP

Azure

Job description

About The Role

The role owns the reliability of production systems serving millions of requests per day — Kubernetes clusters, distributed services, and the CI/CD pipelines that ship them. This is hands‑on infrastructure engineering: running systems at scale, driving down MTTR, and turning incidents into durable engineering improvements.

About The Role

The role owns the reliability of production systems serving millions of requests per day — Kubernetes clusters, distributed services, and the CI/CD pipelines that ship them. This is hands‑on infrastructure engineering: running systems at scale, driving down MTTR, and turning incidents into durable engineering improvements.

You will join a platform team of senior engineers responsible for observability, capacity planning, and automation across a multi-region cloud environment. The work sits at the intersection of software engineering and operations — code, not tickets.

Key Responsibilities

• Build, operate, and scale production Kubernetes clusters (EKS/GKE) across multiple regions, including node autoscaling, cluster upgrades, and workload isolation
• Design and maintain observability infrastructure using Prometheus, Grafana, and OpenTelemetry — dashboards, SLO-based alerting, and actionable paging with minimal noise
• Lead incident response for production outages: drive triage, coordinate communication, write blameless postmortems, and land follow-up fixes
• Automate infrastructure as code with Terraform and CI/CD pipelines in GitHub Actions or ArgoCD, enforcing GitOps workflows across environments
• Define and track reliability targets (SLOs, error budgets) with product teams, and drive capacity planning for services with steep growth trajectories
• Harden production systems: chaos engineering exercises, disaster recovery drills, load testing, and runbook automation
• Write tooling in Go or Python to eliminate toil — self‑service deployment tools, automated failover, and operational health checks

What We Are Looking For

• 3–6 years of experience in SRE, DevOps, or infrastructure engineering, with on‑call ownership of large‑scale production systems
• Deep hands‑on experience with Kubernetes in production, including troubleshooting stateful workloads, networking (CNI, ingress), and performance issues
• Strong programming skills in Go or Python for building operational tooling and automation
• Production experience with at least one major cloud (AWS, GCP, or Azure), including networking, IAM, and cost management
• Solid grounding in systems fundamentals: Linux internals, TCP/IP, load balancing, distributed systems failure modes
• Track record of leading incident response and writing high‑quality postmortems that drive systemic fixes
• Bonus: experience with service meshes (Istio, Linkerd), chaos engineering tools (Gremlin, Litmus), database operations (PostgreSQL, Redis, Kafka), or an active interest in platform engineering and developer experience