Live opening · Posted 7 hours ago

Site Reliability Engineer

Evlo AI · San Francisco, CA (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 7 hours ago
CompanyEvlo AI
LocationSan Francisco, CA (Remote)
Work modeYes
SkillsPython, AWS, GCP, Kubernetes, Terraform
SourceLinkedin
ListedPosted 7 hours ago

About the role

Description supplied by the original job listing.

About The Role
The role owns the reliability, scalability, and operability of production infrastructure serving millions of requests per day — Kubernetes fleets, distributed data stores, and the CI/CD pipelines that ship to them.
You will sit on the front line of production: reducing toil through automation, driving incident response, and setting the SLOs that define how the platform earns user trust. The work spans deep debugging, infrastructure-as-code, and long-term architectural decisions.
Key Responsibilities
Build and maintain Kubernetes-based infrastructure on AWS/GCP using Terraform, Helm, and GitOps workflows (Argo CD or Flux)
Define, instrument, and enforce SLOs/SLIs using Prometheus, Grafana, and OpenTelemetry; build actionable alerting that pages humans only when it matters
Lead incident response for production outages — triage, mitigate, communicate — and drive blameless postmortems through to completed action items
Automate away recurring operational toil with tooling in Go or Python, including self-healing runbooks and capacity management
Harden infrastructure security and reliability: multi-region failover, disaster recovery drills, chaos engineering experiments
Optimize CI/CD pipelines for speed and safety — progressive rollouts, canary analysis, and automated rollback strategies
Partner with product engineering teams on system design reviews, capacity planning, and production readiness
What We Are Looking For
3–7 years of experience in SRE, DevOps, or infrastructure engineering, including running services at significant production scale
Deep hands-on expertise with Kubernetes in production: debugging workloads, managing clusters, and operating at scale
Strong infrastructure-as-code skills with Terraform (or equivalent) and proficiency in Go or Python for tooling and automation
Production experience with observability stacks: Prometheus/Grafana, distributed tracing, and log aggregation at high volume
Solid grasp of distributed systems fundamentals: consensus, queuing, caching, failure modes, and capacity planning
Track record of leading incident response and writing clear, actionable postmortems
Bonus: BS/MS in Computer Science or equivalent practical experience; experience with service mesh (Istio/Linkerd), chaos engineering tools, or platform engineering/IDP work

Work arrangement
Yes

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