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Job Description
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0G is hiring its first dedicated DevOps engineer to own our cloud platform end-to-end: infrastructure, deployments, networking, security hygiene, and cost. Today, that work is spread across several developers.
Our platform runs on five providers: Google Cloud, Alibaba Cloud, AWS, Cloudflare, and Vercel. It includes:
Validator, seed, RPC, and archive nodes for our mainnet and testnet
Confidential-computing (TEE) workloads, GPU machines, and storage nodes
Kubernetes clusters and managed databases
A global RPC load balancer at the edge, and our web apps
All together, that is more than 200 virtual machines. You will be the person who knows what runs where, why it runs there, and what it costs.
What You'll Own
You own the platform, from the network edge to the bill.
Cloud operations: provisioning, upgrades, capacity, and the full resource lifecycle on Google Cloud, Alibaba Cloud, and AWS. That includes rightsizing and releasing what nobody uses.
Kubernetes: run, upgrade, and scale our clusters. Keep them on supported versions and design node pools, autoscaling, and Spot capacity.
Blockchain node fleet: operate validator, sentry, seed, RPC, and archive nodes, including peering topology, snapshots, sync, and client upgrades.
Networking and edge: VPC design, load balancers, DNS, Cloudflare Workers, Tunnels, and WAF, and keeping internet egress deliberate and cheap.
Infrastructure as code and CI/CD: every environment defined in Terraform or Pulumi. You 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.
Observability and on-call: metrics, logs, alerts, and dashboards, including control of metric cardinality. You also run incident response and write the postmortems.
Security and access: least-privilege IAM across every provider, secrets management, and no databases or admin ports open to the internet.
Cost management: billing exports, budgets and alerts, tagging, a monthly cost review, and commitment planning.
Developer enablement: templates, preview environments, documentation, and support for the engineers who ship on the platform.
Our Stack
Kubernetes: GKE, EKS, Helm, Ingress, and Gateway API, autoscaling, RBAC, network policies
Networking: TCP/IP, subnets and CIDR, routing, NAT, L4 and L7 load balancers, DNS, TLS, firewalls, VPC peering
Google Cloud: Compute Engine, GKE, Cloud SQL, Cloud Run, IAM, Cloud Monitoring, billing export to BigQuery
Infrastructure as code: Terraform, Pulumi
CI/CD and containers: Jenkins or an equivalent (GitHub Actions, GitLab CI), Argo CD, Docker and BuildKit, container registries
Observability: Prometheus, Grafana, Cloud Monitoring, CloudWatch, Alibaba CloudMonitor
Linux: Systems administration, systemd, disks and filesystems, performance debugging
Alibaba Cloud: ECS, VPC, NLB and ALB, ESSD disks, RDS, PolarDB, SAE, Cloud Firewall
AWS: EC2, EKS, RDS, ALB and NLB, Route 53, S3, Organizations
Cloudflare: DNS, Workers, Tunnels, WAF and rate limiting, Zero Trust
Databases (operations): PostgreSQL, MySQL, MongoDB, managed Kafka
Blockchain nodes: CometBFT-based chains, reth and other EVM clients, P2P networking
Vercel: Projects, builds, ISR, team access
Confidential computing: Intel TDX virtual machines on Google Cloud and Alibaba Cloud
Must-Haves
We want 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.
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.
CI/CD, in depth
Pipeline design: you have built and run production CI/CD on Jenkins or an equivalent (GitHub Actions, GitLab CI, CircleCI, Tekton). Pipelines are 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. That includes 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 our chain: building and publishing node binaries and images, and coordinating rolling upgrades across validator and RPC fleets.
Delivery health: you track build time, build cost, flaky tests, and DORA metrics (deployment frequency, lead time, change failure rate, time to restore), and you cut 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.
Also required
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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0G Labs
View Company Profile0G Labs (operating under 0g.ai, legally Zero Gravity Labs, Inc.) is the premier, enterprise-grade decentralized AI operating system (deAIOS), Artificial Intelligence Layer 1 (AIL) pioneer, and high-performance Web3 data infrastructure powerhouse engineered to act as the definitive, high-velocity data availability, modular storage, and verifiable compute layer for next-generation on-chain autonomous agents, deep learning networks, and scaling dApps. Founded by technology innovators Michael Heinrich and Ming Wu, the platform completely eliminates the severe systemic friction of modern AI development—where builders are trapped in centralized, opaque black-box cloud environments and legacy blockchain scaling limits that drop momentum when processing data-heavy AI workloads—by deploying an advanced, multi-layered decentralized network. Moving far beyond traditional, passive smart contract storage networks or basic GPU marketplaces, 0G natively unifies an ultra-high-throughput data availability (DA) layer achieving a staggering 50 GB per second throughput, decentralized data storage optimized for massive training sets, trustless GPU compute marketplaces running inside hardware-secured Trusted Execution Enclaves (TEEs), and its EVM-compatible 0G Chain into a single high-availability Web3 AI stack. Powering over 400 million transactions across its testnets and anchoring an expansive ecosystem of more than 300 global partners—including major networks like Alibaba, Stanford Blockchain, and Optimism—the infrastructure handles intensive model training and real-time inference with production-hardened cryptographic precision. Validating its sector-defining authority, 0G Labs has secured more than $425 million in massive institutional financing, including a $40 million seed round led by Hack VC alongside Delphi Ventures, OKX Ventures, Samsung Next, and Animoca Brands, combined with a monumental $350 million growth round in June 2025 and an $88.88 million ecosystem foundation allocation. Under the hood, its technology core utilizes sophisticated Zero-Knowledge (ZK) validation loops, the Geth-to-Reth accessibility architecture, and its signature browser-native App Studio (app.0g.ai) built to allow developers to build, secure, and deploy live AI applications using cryptographic root hashes without relying on centralized databases. What sets 0G Labs apart is its uncompromising dedication to replacing fragile, siloed corporate infrastructure dependencies with absolute data availability scale, verified decentralized machine learning, and ledger-to-model connectivity velocity; by bridging the gap between performance-intensive structural AI computation and immediate trustless Web3 execution, the enterprise remains the definitive cornerstone of modern algorithmic decentralized intelligence and global Web3 transformation.
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