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Senior DevOps Engineer

0G
Contract type
Ongoing
Work mode
Remote
Experience
Senior · 5+ years

Job description

0G is hiring its first dedicated DevOps engineer to own the cloud platform end to end, covering infrastructure, deployments, networking, security hygiene and cost across five cloud providers. The role owns the platform from the network edge to the bill, including Kubernetes clusters, blockchain node fleets and CI/CD.

At a glance

Work mode
Remote

What you'll do

  • Own cloud operations: provisioning, upgrades, capacity and the full resource lifecycle on Google Cloud, Alibaba Cloud and AWS, including rightsizing and releasing what nobody uses
  • Run, upgrade and scale Kubernetes clusters, keep them on supported versions and design node pools, autoscaling and Spot capacity
  • Operate validator, sentry, seed, RPC and archive nodes, including peering topology, snapshots, sync and client upgrades
  • Handle networking and edge: VPC design, load balancers, DNS, Cloudflare Workers, Tunnels and WAF, and keeping internet egress deliberate and cheap
  • Define every environment in Terraform or Pulumi and design and run CI/CD on Jenkins or an equivalent such as GitHub Actions or GitLab CI, covering builds, tests, security scans and releases from commit to production, with no manual steps
  • Own observability and on-call: metrics, logs, alerts and dashboards, including control of metric cardinality; run incident response and write postmortems
  • Maintain security and access: least-privilege IAM across every provider, secrets management, and no databases or admin ports open to the internet
  • Manage cost: billing exports, budgets and alerts, tagging, a monthly cost review and commitment planning
  • Enable developers: templates, preview environments, documentation and support for the engineers who ship on the platform

What we're looking for

  • 5+ years in DevOps, SRE or platform roles, including 3+ years running production Kubernetes and owning CI/CD pipelines
  • Kubernetes in depth: upgrading control planes and node pools with no downtime and keeping clusters on supported versions
  • Kubernetes scheduling: requests and limits, affinity, taints and tolerations, priority, and eviction under node pressure
  • Autoscaling with the HPA, cluster autoscaler or Karpenter, plus Spot or preemptible node pools for non-critical work
  • Networking inside the cluster: CNI, Services, Ingress or Gateway API, network policies, and DNS within the cluster
  • Security: RBAC, Pod Security, workload identity, and secrets that never sit in plain environment variables
  • Stateful workloads: StatefulSets, persistent volumes and CSI drivers, and backup and restore
  • Packaging and delivery with Helm or Kustomize, ideally through GitOps with Argo CD or Flux
  • Debugging a failing pod, node or rollout from events, logs and metrics
  • Pipeline design: built and run production CI/CD on Jenkins or an equivalent (GitHub Actions, GitLab CI, CircleCI, Tekton), with pipelines defined as code in a Jenkinsfile or workflow YAML, with shared libraries and reusable templates
  • CI platform operations: running Jenkins controllers with ephemeral agents on Kubernetes, or self-hosted runners, including plugin and version upgrades, credential handling, and scaling build capacity
  • Build pipelines: multi-service and monorepo builds with caching and parallel stages, and versioned artifacts; container images built with Docker, BuildKit or Kaniko, including multi-architecture images, image scanning, SBOMs and signing
  • Deployment pipelines: promotion from dev to staging to production with approvals and quality gates, plus blue-green, canary and fast rollback; GitOps with Argo CD or Flux, and database migrations as part of a release
  • Infrastructure pipelines: Terraform or Pulumi plan and apply from CI, with policy checks and drift detection
  • Pipeline security: short-lived credentials through OIDC federation or a secrets vault instead of long-lived keys, least-privilege deploy roles, and protected branches
  • Release engineering for the chain: building and publishing node binaries and images, and coordinating rolling upgrades across validator and RPC fleets
  • Delivery health: tracking build time, build cost, flaky tests and DORA metrics (deployment frequency, lead time, change failure rate, time to restore), and cutting wasted builds with ignore rules and caching
  • Networking fundamentals: TCP/IP, subnetting and CIDR, routing, NAT, and the difference between L4 and L7 load balancing
  • DNS, TLS and certificates, firewalls and security groups
  • Private connectivity: VPC design, peering, private endpoints, and keeping internal traffic off public IPs
  • Troubleshooting with dig, curl, mtr and tcpdump, and understanding what internet egress costs
  • Production experience on at least two of Google Cloud, AWS and Alibaba Cloud, and willingness to learn the third quickly
  • Terraform or Pulumi in production, plus scripting in Bash and in Python or Go
  • A track record of cutting a cloud bill with data, through rightsizing, cleanup or commitments
  • A security-first habit with production credentials, and clear written communication

Nice to have

  • Running blockchain nodes in production, such as CometBFT validators and sentries, EVM archive or RPC nodes, and snapshot pipelines
  • Cloudflare Workers, Tunnels and Zero Trust at scale
  • Alibaba Cloud on the international site, including its billing and support model
  • Confidential computing (Intel TDX) and GPU workloads
  • CKA or CKS certification, a FinOps certification, or experience moving a team between CI systems, such as Jenkins to GitHub Actions
  • Go or Rust, enough to read and patch the services you operate

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About the company

Mission

Making AI a public good

Key facts

  • Platform runs on five providers: Google Cloud, Alibaba Cloud, AWS, Cloudflare and Vercel
  • Platform includes validator, seed, RPC, and archive nodes for mainnet and testnet
  • Platform includes confidential-computing (TEE) workloads, GPU machines and storage nodes
  • Platform includes Kubernetes clusters and managed databases
  • Platform includes a global RPC load balancer at the edge, and web apps
  • More than 200 virtual machines

What they value

  • Purpose: The opportunity to contribute to making AI a public good
  • Growth: A self-directed environment where you can take initiative to shape your role and career