Position OverviewWe are seeking a visionary and hands-on Cloud SRE Architect to lead the design, development, and evolution of our next-generation public cloud platform. This role will oversee the end-to-end architecture across CPU, GPU, RDS, storage, networking, serverless, and AI services, ensuring global scalability, reliability, and performance. The ideal candidate is a strategic thinker with deep technical expertise in cloud infrastructure, platform engineering and AI systems, capable of bridging architecture vision with real-world engineering execution. You will collaborate closely with cross-functional teams and global partners to define our cloud technology roadmap, optimize multi-region deployments, and deliver world-class infrastructure and platform solutions that power large-scale AI and enterprise workloads.
Key ResponsibilitiesYou will own 1-2 of these:
- Collection & Storage: collection-agent, customer-sdk-gateway, metrics-store, logs-store, traces-store, profiles-store, analytics-lake, enrichment-service, collection-monitor.
- Alert, Correlation & SLO: alert-engine-framework, alert-correlation, slo-framework, default M-series alert rules.
- Topology, Cluster-Health & Cluster Platform Services: topology-service, cluster-health-rollup, OSS-SRE-tool collection plugins for K8s, Slurm, Ray, Volcano, Kueue, and KubeRay.
- Fault-Prediction: prediction-engine-framework and built-in predictors (GPU, Link, Disk, XPA, Straggler, SDC, Stranded GPU).
- Remediation, Workflow, Inspection & Jobs: remediation-actuator, orchestration-substrate (workflow engine), inspection-orchestrator, job-scheduler, NCCL-baseline inspection probe.
- Hardware Lifecycle & DC Ops: hardware-lifecycle, dc-operations, boot-provisioning, rolling-upgrade, bare-metal-bmc-service, auto-discovery, ZTP D0-D5 pipeline, IPMI bare-metal management.
- Identity, Secrets, Tenant-Config & CMDB: iam-service, secrets-service, tenant-sre-config, cmdb-cache, schema registry.
- Customer-Bridge, Ticketing & SRE Platform Portal: customer-bridge, customer-ticketing, sre-operation-system, Customer Console BFF, SRE Console BFF.
- Backup, DR & Meta-Monitor: backup-orchestrator, meta-monitor, external-watcher integration (Datadog or equivalent).
- CI/CD, GitOps, Plugin Framework & SRE Image Registry: cicd-pipeline, gitops-sync, plugin-registry, sre-image-registry.
- Self-Improving Agent: agent-control-plane, agent-discovery, agent-codegen, agent-sandbox, per-Region LLM gateway.
- Global SRE Management: maintenance-window-orchestrator, change-management, capacity-planner, cost-optimizer, gpu-efficiency-dashboard, network-stability-dashboard, patching-orchestrator, artifact-management, compat-matrix-service, security-platform.
Qualifications- Software Engineering Experience: 7+ years of production software engineering experience, including 2 or more years operating what you built (real on-call experience, not just shipping code).
- Programming Languages: Production-depth mastery of at least one systems-grade language-Go (preferred), Rust, or Java. Proficiency in Python for tooling and SDK work.
- Distributed Systems Fundamentals: Strong grasp of at-least-once vs. exactly-once trade-offs, idempotency, back-pressure, leader election, consistent hashing, gossip, and fan-out. Ability to evaluate CRDT vs. Raft vs. Paxos and select the right tool for the job.
- Multi-Region Observability Stack: Experience at production scale with Prometheus, VictoriaMetrics, Mimir, Thanos, Loki, Elasticsearch, Tempo, Jaeger, or OpenTelemetry. Must have built or substantively contributed to the ingest, query, or storage paths of these systems.
- GitOps & CI/CD: Hands-on experience with Argo, Flux, Helm, Kustomize, Cosign signing, signed-bundle promotion, and blast-radius-aware rollouts.
- Kubernetes Operator Pattern: Proven experience writing a controller or CRD handling real production traffic, with a deep understanding of watch-cache mechanics, leader election, and reconcile loops.
- mTLS & Secrets Management: Experience executing end-to-end mTLS bootstrap with certificate rotation. Hands-on experience with HashiCorp Vault or cloud KMS (AWS KMS / GCP KMS).
- SQL & Time-Series Data: Ability to read a Prometheus query plan, build a recording-rule strategy, and write SQL that joins per-tenant telemetry against analytics-lake tables.
- Testing Discipline: Rigorous approach to unit, integration, contract, chaos, and soak testing. Experience writing and maintaining your own comprehensive tests.
- Technical Writing Fluency: Ability to author clear design docs that align with existing platform architecture, create runbooks optimized for 3 AM on-call responses, and write intent-driven PR descriptions.
Preferred Qualifications (GPU / AI-Infra Context)
Experience in at least one of the following areas is a strong plus:- NVIDIA Internals: Deep understanding of DCGM and NVIDIA driver internals, including XID semantics and MIG / vGPU partitioning.
- Networking & Fabrics: Experience with InfiniBand or RoCE fabrics, including subnet managers, partitioning, optical health, and NCCL collective tracing.
- HPC Storage: Experience managing Lustre, NetApp, Pure, DDN, VAST, or NVMe-oF under multi-tenant loads.
- Hardware Management: Hands-on experience with BMC, IPMI, and Redfish at OEM scale (Supermicro, Dell, HPE, Lenovo).
- Cluster Platform Internals: Familiarity with Kubernetes GPU Operator, Slurm controller, or Ray GCS.
- BS/MS in Computer Science or similar
- Hyperscale or NeoCloud experience
