Senior SRE, Automation Engineer – Customer Facing

Job not on LinkedIn

🔥 0 minutes ago

🏄 California, Texas – Remote

🏄 California – Remote 🤠 Texas – Remote

💵 $180k - $260k / year

⏰ Full Time

🟠 Senior

🤖 QA Automation Engineer

👻 Ghost score 5%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Bitdeer Group

WebsiteLinkedInAll Job Openings

201 - 500 employees

💼 Consulting

📦 Logistics

🏗️ Construction

💰 Post-IPO Equity on 2023-05

Consulting • Logistics • Construction

Bitdeer Group is a leader in the blockchain and high-performance computing industry. It is one of the world’s largest holders and suppliers of hash rate, offering specialized mining infrastructure and high-quality hash rate sharing products. Founded by cryptocurrency pioneer Jihan Wu and led by CEO Matt Linghui Kong, the company is headquartered in Singapore with mining datacenters in the United States, Norway, and Bhutan. Bitdeer is committed to providing comprehensive computing solutions, including cloud services and AI capabilities, while emphasizing dedication, authenticity, and trustworthiness in its mission to be the most reliable provider in the industry.

📋 Description

• Own end-to-end reliability of the customer-facing GPU cloud service, including availability, job completion, provisioning latency, and tenant experience • Operate production Kubernetes clusters optimized for GPU workloads at 100–10,000 GPUs • Manage Nvidia GPU operator, device plugin, MIG configuration, GPU time-slicing, and multi-tenant GPU allocation policies • Implement topology-aware scheduling based on GPU locality, NVLink domains, and network rail affinity • Manage tenant onboarding, quotas, isolation enforcement, and offboarding/reclamation • Automate Bare-Metal-as-a-Service provisioning, tenant handoff, lifecycle, and reclamation • Define and publish customer-facing SLIs, SLOs, and SLAs • Lead incident detection, remediation, escalation, customer-facing status updates, and post-incident reviews • Build and operate tenant-aware monitoring and observability with Prometheus, Grafana, Alertmanager, and PagerDuty • Automate GPU node failure detection, drain/cordon/taint, and workload rescheduling • Develop infrastructure-as-code using Terraform, Helm, and GitOps across GPU clusters • Create service documentation, tenant runbooks, capacity plans, and support tiering • Partner with customer success and support to convert customer-reported issues into systemic improvements • Build self-service observability for customer status, quota, and job health • Make the control plane safe for automated remediation through CRDs and executable runbooks • Deliver published and met SLAs, automated GPU-fault recovery, external-tenant BMaaS onboarding, reduced MTTD/MTTR, and tenant self-service observability

🎯 Requirements

• 5+ years in SRE / cloud operations, with at least 2 years operating GPU workloads at scale • Deep understanding of Kubernetes operations and GPU workload management, including Nvidia GPU operator, device plugin, MIG, time-slicing, and GPU scheduling • Experience with topology-aware scheduling and GPU-specific resource management • Hands-on experience building multi-tenant cloud platforms with strong isolation guarantees • Customer-facing cloud service experience defining and operating against customer SLAs/SLOs, handling tenant incidents and communications • Experience with bare-metal server provisioning and lifecycle automation using Ironic, MAAS, or custom solutions • Proficiency in Terraform, Helm, and GitOps workflows using ArgoCD or Flux • Strong SRE background including SLI/SLO/SLA frameworks, error budgets, incident management, and capacity planning • Experience with Prometheus, Grafana, and alerting at scale • Strong programming skills in Go or Python for automation/operator development • AIOps aptitude: treating the control plane as an execution surface for automated remediation • Runbook-as-code mindset: SRE playbooks should be executable by the platform