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Tomorrow.io is seeking a DevOps Engineer to power the reliability, security, and efficiency of their weather platform. You'll build self-service platforms that enable developers and weather scientists to work independently, integrate AI into operational processes, and collaborate with R&D to optimize performance and scale.
Key responsibilities include evolving and maintaining cloud infrastructure, delivery pipelines, and observability systems; developing AI-powered tools to improve development and operations efficiency; partnering with platform engineering teams to enhance service performance, reliability, scale, security, and cost; maintaining production SLOs through on-call rotations and incident follow-through; and contributing to team knowledge-sharing and continuous improvement.
Required experience: 4+ years as a DevOps/Site Reliability Engineer, including 2+ years hands-on with major cloud platforms (GCP, AWS, or Azure) and Infrastructure as Code (Terraform, Crossplane, or Kubernetes-native approaches). You'll need production Kubernetes depth covering containerized deployments, scheduling, resource management, and troubleshooting; end-to-end CI/CD pipeline ownership with modern tooling and advanced deployment methodologies; hands-on experience implementing and customizing monitoring and observability systems (Datadog, Grafana + Loki, Prometheus, ELK); software engineering craft to review and improve AI agent outputs; active hands-on use of AI tooling in engineering work; and a product mindset with deep responsibility for service reliability.
Tech stack: GCP (primary), Azure, AWS, Linux, Kubernetes (GKE/AKS), Helm, KEDA, Argo Workflows, External Secrets, Cloud Run, Cloud Functions, Terraform, Crossplane, GitHub Actions, ArgoCD, Datadog, Grafana + Loki, PostgreSQL/PostGIS, MongoDB Atlas, Redis, Pub/Sub, GCS, S3, Cloudflare, Kong Gateway, Google LB, CloudFront, Python, Go, Node.js, and React.
The role offers rapid growth in technical depth and responsibility within a culture where engineers own their production workloads end-to-end. You'll work on complex, high-scale problems with sharp minds in the industry, helping teams deliver faster and more safely while building the world's most trusted weather platform.
