Site Reliability Engineer

All roles at JumpCloud® are Remote unless otherwise specified in the Job Description.

About JumpCloud®

JumpCloud® is the AI-powered unified IT management platform designed to secure the modern workforce. By consolidating identity, device, and access management, JumpCloud provides intelligent, secure IT that scales from human users to autonomous AI agents. We help organizations around the globe eliminate complexity and turn AI risk into an optimized advantage, ensuring the right people and agents have secure access to the right resources at all times.  

JumpCloud is Intelligent, Secure IT.

What You’ll Be Doing:

• Architect, scale, and continuously improve the reliability, availability, and performance of JumpCloud’s multi-region microservices, APIs, and authentication infrastructure (AWS/GCP).

• Architect, build, and maintain Disaster Recovery (DR) process, multi-region failover automation, and business continuity strategies to ensure rapid recovery against strict RTO and RPO objectives.

• Lead the design and enforcement of SLIs, SLOs, and Error Budget frameworks across multi-disciplinary engineering teams.

• Drive end-to-end observability strategy using Datadog, implementing actionable Golden Signals monitoring to drastically reduce MTTD/MTTR and eliminate alert fatigue.

• Lead on-call escalation, major incident management, and drive strict adherence to 99.99% availability SLAs.

• Facilitate blameless post-incident reviews, executing systemic root-cause remediations to prevent recurring failure modes.

• Architect, manage, and scale production Kubernetes (EKS) clusters, implementing advanced GitOps workflows (Argo CD, Kargo) and deployment patterns.

• Design and maintain modular, enterprise-grade Infrastructure-as-Code using Terraform across multi-account, multi-region cloud environments.

• Design, build, and maintain interactive FinOps and cost-optimization dashboards to provide engineering and leadership teams with actionable insights into multi-cloud spend, unit economics, and resource utilization.

• Eliminate complex operational toil by writing production-grade Python or Go tooling, platform automation, and custom integrations.

• Champion AI-assisted software development workflows (Cursor, Claude Code, GitHub Copilot) to accelerate automation, runbook creation, and incident triage across the team.

• Author operational runbooks, architecture decision records, and mentor mid-level/junior engineers to raise the overall technical bar.