Member of Technical Staff, DevOps

Reactor is building an inference platform for real-time world models. The DevOps/SRE engineer will own and improve the AI platform’s reliability, delivery pipelines, infrastructure, observability, and incident response.

Responsibilities

• Own and evolve our CI/CD pipelines: dynamic pipeline generation across a monorepo of Go services, Python model containers, and Helm charts
• Operate and improve our GitOps deployment lifecycle: Helm releases, Kustomizations, and image automation across multiple clusters
• Build and maintain our observability stack: distributed tracing, metrics, dashboards, and alerting across all services and GPU workloads
• Define and track SLOs for core platform services, including session latency, model cold start time, and streaming reliability
• Run incident response: triage production issues, write postmortems, build runbooks, and drive reliability improvements
• Manage infrastructure-as-code across multiple cloud providers and regions: plan/apply workflows, state management, drift detection
• Operate secret management: encrypted secrets, external secret syncing, certificate automation
• Improve deployment safety: canary rollouts, health checks, startup probes, rollback automation
• Manage authentication infrastructure: OIDC federation for CI, workload identity for cloud services, cross-cloud credential management
• Participate in on-call rotation and build the tooling that makes on-call less painful

Skills

• You've run production Kubernetes clusters and been on-call for them
• Strong CI/CD experience: you've built and maintained pipelines for monorepos, not just single-service repos
• GitOps experience: you understand reconciliation loops, drift detection, and why image automation matters
• Infrastructure-as-code fluency with Terraform or similar across multiple environments and cloud accounts
• You know observability beyond just "set up dashboards". You've defined SLOs, built alerting that doesn't page on noise, and used traces to debug cross-service latency issues
• Comfortable with secret management patterns (KMS, encrypted configs, external secret operators)
• Incident response experience: you've triaged production outages, written postmortems that actually led to improvements, and built runbooks that other engineers could follow
• You write code, not just YAML. Proficiency in Go, Python, or Bash for building tooling, automation, and pipeline scripts
• Experience with GPU workloads on Kubernetes: device plugins, GPU-aware scheduling, GPU monitoring
• Multi-cloud operations beyond a single provider
• Real-time or streaming workloads: low-latency systems where p99 matters more than average
• Experience with Helm chart authoring and managing complex value layering across environments
• Familiarity with real-time media or relay infrastructure
• FinOps experience: GPU cost optimization, spot/preemptible instance management

Benefits

• Meaningful early equity
• Visa sponsorship
• Relocation support
• Generous health, dental, and vision coverage

Company Overview

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